ORCID Profile
0000-0001-7648-6447
Current Organisation
Rowan University
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Biological Psychology (Neuropsychology, Psychopharmacology, Physiological Psychology) | Sensory Processes, Perception and Performance | Psychology
Publisher: Cold Spring Harbor Laboratory
Date: 13-11-2019
DOI: 10.1101/841353
Abstract: Many decisions, from crossing a busy street to choosing a profession, require integration of discrete sensory events. Previous studies have shown that integrative decision-making favours more reliable stimuli, mimicking statistically optimal integration. It remains unclear, however, whether reliability biases are automatic or strategic. To address this issue, we asked observers to reproduce the average motion direction of two suprathreshold coherent motion signals, presented successively and varying in reliability. Although unbiased responses were both optimal and possible by virtue of task rules and suprathreshold motion coherence, we found robust behavioural biases favouring the more reliable stimulus. Using population-tuning modelling of brain activity recorded using electroencephalography, we characterised tuning to the average motion direction. In keeping with the behavioural biases, the tuning profiles also exhibited reliability biases. Taken together, our findings reveal that temporal integration of discrete sensory events is automatically and sub-optimally weighted according to stimulus reliability.
Publisher: Proceedings of the National Academy of Sciences
Date: 02-2023
Abstract: A canonical feature of sensory systems is that they adapt to prolonged or repeated inputs, suggesting the brain encodes the temporal context in which stimuli are embedded. Sensory adaptation has been observed in the central nervous systems of many animal species, using techniques sensitive to a broad range of spatiotemporal scales of neural activity. Two competing models have been proposed to account for the phenomenon. One assumes that adaptation reflects reduced neuronal sensitivity to sensory inputs over time (the “fatigue” account) the other posits that adaptation arises due to increased neuronal selectivity (the “sharpening” account). To adjudicate between these accounts, we exploited the well-known “tilt aftereffect”, which reflects adaptation to orientation information in visual stimuli. We recorded whole-brain activity with millisecond precision from human observers as they viewed oriented gratings before and after adaptation, and used inverted encoding modeling to characterize feature-specific neural responses. We found that both fatigue and sharpening mechanisms contribute to the tilt aftereffect, but that they operate at different points in the sensory processing cascade to produce qualitatively distinct outcomes. Specifically, fatigue operates during the initial stages of processing, consistent with tonic inhibition of feedforward responses, whereas sharpening occurs ~200 ms later, consistent with feedback or local recurrent activity. Our findings reconcile two major accounts of sensory adaptation, and reveal how this canonical process optimizes the detection of change in sensory inputs through efficient neural coding.
Publisher: Research Square Platform LLC
Date: 25-08-2020
DOI: 10.21203/RS.3.RS-1965199/V1
Abstract: The ability to make accurate and timely decisions, such as judging when it is safe to cross the road, is the foundation of adaptive behaviour. While the computational and neural processes supporting simple decisions on isolated stimuli have been well characterised, in the real world decision-making often requires integration of discrete sensory events over time and space. When crossing the road, for ex le, the locations and speeds of several cars must be considered. It remains unclear how such integrative perceptual decisions are regulated computationally. Here we used psychophysics, electroencephalography and computational modelling to understand how the human brain combines visual motion signals across space. We directly tested competing predictions arising from influential serial and parallel accounts of visual processing. Using a biologically plausible model of motion filtering, we find evidence in favour of parallel integration as the fundamental computational mechanism regulating integrated perceptual decisions.
Publisher: Research Square Platform LLC
Date: 30-01-2023
DOI: 10.21203/RS.3.RS-1965199/V2
Abstract: The ability to make accurate and timely decisions, such as judging when it is safe to cross the road, is the foundation of adaptive behaviour. While the computational and neural processes supporting simple decisions on isolated stimuli have been well characterised, in the real-world decision-making often requires integration of discrete sensory events over time and space. When crossing the road, for ex le, the locations and speeds of several cars must be considered. It remains unclear how such integrative perceptual decisions are regulated computationally. Here we used psychophysics, electroencephalography and computational modelling to understand how the human brain combines visual motion signals across space. We directly tested competing predictions arising from influential serial and parallel accounts of visual processing. Using a biologically plausible model of motion filtering, we find evidence in favour of parallel integration as the fundamental computational mechanism regulating integrated perceptual decisions.
Publisher: Research Square Platform LLC
Date: 24-07-2023
DOI: 10.21203/RS.3.RS-1965199/V3
Abstract: The ability to make accurate and timely decisions, such as judging when it is safe to cross the road, is the foundation of adaptive behaviour. While the computational and neural processes supporting simple decisions on isolated stimuli have been well characterised, in the real-world decision-making often requires integration of discrete sensory events over time and space. When crossing the road, for ex le, the locations and speeds of several cars must be considered. It remains unclear how such integrative perceptual decisions are regulated computationally. Here we used psychophysics, electroencephalography and computational modelling to understand how the human brain combines visual motion signals across space. We directly tested competing predictions arising from influential serial and parallel accounts of visual processing. Using a biologically plausible model of motion filtering, we find evidence in favour of parallel integration as the fundamental computational mechanism regulating integrated perceptual decisions.
Publisher: American Chemical Society (ACS)
Date: 04-12-2017
Abstract: The development of advanced thermal transport materials is a global challenge. Two-dimensional nanomaterials have been demonstrated as promising candidates for thermal management applications. Here, we report a boron nitride (BN) nanosheet olymer composite film with excellent flexibility and toughness prepared by vacuum-assisted filtration. The mechanical performance of the composite film is highly flexible and robust. It is noteworthy that the film exhibits highly anisotropic properties, with superior in-plane thermal conductivity of around 200 W m
Publisher: American Psychological Association (APA)
Date: 02-2022
DOI: 10.1037/XLM0000914
Abstract: Integrating evidence from multiple sources to guide decisions is something humans do on a daily basis. Existing research suggests that not all sources of information are weighted equally in decision-making tasks, and that observers are subject to biases in the face of internal and external noise. Here we describe two experiments that measured observers' ability to integrate successive visual signals. Participants viewed pairs of gratings presented sequentially and reproduced their average orientation. Experiment 1 revealed a recency bias in evidence integration, such that observers' average judgments were closer to the orientation of the second grating than the first. Mixture distribution modeling revealed that this was caused by a recency bias in averaging, as well as a tendency to disregard the first stimulus altogether in some trials. In Experiment 2 we replicated these findings, and quantified orientation-specific patterns of neural activity recorded during the task using population-tuning curve modeling of electroencephalography data. This analysis yielded robust orientation tuning to both the presented gratings and observers' decisions, and suggested that observers were storing both grating stimuli for subsequent averaging rather than computing a running average. The neural representation of the second grating was not reliably stronger than that of the first, suggesting that the recency bias is not due to a difference in the strength of encoding of the second stimulus, and instead may arise at a later decision stage where information is retrieved or integrated. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Publisher: Cold Spring Harbor Laboratory
Date: 02-2019
DOI: 10.1101/537910
Abstract: The ability to select and combine multiple sensory inputs in support of accurate decisions is a hallmark of adaptive behaviour. Attentional selection is often needed to prioritize stimuli that are task-relevant and to attenuate potentially distracting sources of sensory information. As most studies of perceptual decision-making to date have made use of task-relevant stimuli only, relatively little is known about how attention modulates decision making. To address this issue, we developed a novel ‘integrated’ decision-making task, in which participants judged the average direction of successive target motion signals while ignoring concurrent and spatially overlapping distractor motion signals. In two experiments that varied the role of attentional selection, we used linear regression to quantify the influence of target and distractor stimuli on behaviour. Using electroencephalography, we characterised the neural correlates of decision making, attentional selection and feature-specific responses to target and distractor signals. While targets strongly influenced perceptual decisions and associated neural activity, we also found that concurrent and spatially coincident distractors exerted a measurable bias on both behaviour and brain activity. Our findings suggest that attention operates as a real-time but imperfect filter during perceptual decision-making by dynamically modulating the contributions of task-relevant and irrelevant sensory inputs.
Publisher: Society for Neuroscience
Date: 29-07-2021
Publisher: Cold Spring Harbor Laboratory
Date: 24-01-2023
DOI: 10.1101/2023.01.23.525278
Abstract: Visual working memory is critical for goal-directed behaviour as it maintains continuity between previous and current visual input. Functional neuroimaging studies have shown that visual working memory relies on communication between distributed brain regions, which implies an important role for long-range white matter connections in visual working memory performance. Here, we characterised the relationship between the microstructure of white matter association tracts and the precision of visual working memory representations. To that purpose, we devised a delayed estimation task which required participants to reproduce visual features along a continuous scale. A s le of 80 healthy adults performed the task and underwent diffusion-weighted MRI. We applied mixture distribution modelling to quantify the precision of working memory representations and guess rates, both of which contribute to observed responses. Latent components of tract-specific microstructural indices were identified by principal component analysis. Higher working memory precision was associated with lower bulk diffusion across ten tracts of interest and higher directionality of diffusion in a group of frontoparietal-occipital tracts. Importantly, there was no association between guess rates and any of the structural components. Our findings suggest that microstructural properties of white matter tracts connecting posterior and frontal brain regions mediate, in a functionally specific manner, the precision of visual working memory.
Publisher: Elsevier BV
Date: 05-2023
Start Date: 06-2012
End Date: 12-2018
Amount: $2,649,836.00
Funder: Australian Research Council
View Funded ActivityStart Date: 12-2022
End Date: 12-2025
Amount: $565,230.00
Funder: Australian Research Council
View Funded Activity