Decomposition of neural circuits of human attention using a model based analysis: sSoTs model application to fMRI data

The complex neural circuits found in fMRI studies of human attention were decomposed using a model of spiking neurons. The model for visual search over time and space (sSoTS) incorporates different synaptic components (NMDA, AMPA, GABA) and a frequency adaptation mechanism based on IAHP current. This frequency adaptation current can act as a mechanism that suppresses the previously attended items. It has been shown [1] that when the passive process (frequency adaptation) is coupled with a process of active inhibition, new items can be successfully prioritized over time periods matching those found in psychological studies. In this study we use the model to decompose the neural regions mediating the processes of active attentional guidance, and the inhibition of distractors, in search. Activity related to excitatory guidance and inhibitory suppression was extracted from the model and related to different brain regions by using the synaptic activation from sSoTS’s maps as regressors for brain activity derived from standard imaging analysis techniques. The results show that sSoTS pulls-apart discrete brain areas mediating excitatory attentional guidance and active distractor inhibition

Cross-cultural differences in visual attention: a computational modelling study

Literature in visual perception has identified that there are cross-cultural differences in visual perception [1]. Research comparing members of interdepended and collectivist East Asian cultures with independent and individualist European American cultures into picture perception showed that East Asians are more likely to attend the perceptual field as a whole and to focus on context and Westerns to focus on the salient foreground objects [1]. Research on cross-cultural differences has focused on investigating cross-cultural differences related to bottom-up information. Furthermore, research that experimentally manipulated the cultural norms of individualism and collectivism groups managed to attenuate cultural-specific preferences for social factors beneficial in human motivation [2]. Investigating the underlying mechanisms involved in these differences is very important as it can affect everyday tasks, advertisement and many other aspects of our everyday life. Here we present the first steps of this work, investigating the underlying processes in cross-cultural differences using computational modelling studies. The computational model is based on the spiking Search over Space and Time (sSoTS) model [3], that has been used to simulate Visual Attention task. sSoTS has incorporated mechanisms that allows us to investigate both bottomup and top-down processes. We show that sSoTS can successfully simulate cross-cultural differences in Visual attention involving bottom-up tasks. Moreover, we expand the studies by making predictions from the computational modelling studies for cross-cultural differences and top-down tasks

Temporal Binding and Segmentation in Visual Search: A Computational Neuroscience Analysis

Human visual search operates not only over space but also over time, as old items remain in the visual field and new items appear. Preview search (where one set of distractors appears before the onset of a second set) has been used as a paradigm to study search over time and space [Watson, D. G., & Humphreys, G. W. Visual marking: Prioritizing selection for new objects by top–down attentional inhibition of old objects. Psychological Review, 104, 90–122, 1997], with participants showing efficient search when old distractors can be ignored and new targets prioritized. The benefits of preview search are lost, however, if a temporal gap is introduced between a first presentation of the old items and the re-presentation of all the items in the search display [Kunar, M. A., Humphreys, G. W., & Smith, K. J. History matters: The preview benefit in search is not onset capture. Psychological Science, 14, 181–185, 2003a], consistent with the old items being bound by temporal onset to the new stimuli. This effect of temporal binding can be eliminated if the old items reappear briefly before the new items, indicating also a role for the memory of the old items. Here we simulate these effects of temporal coding in search using the spiking search over time and space model [Mavritsaki, E., Heinke, D., Allen, H., Deco, G., & Humphreys, G. W. Bridging the gap between physiology and behavior: Evidence from the sSoTS model of human visual attention. Psychological Review, 118, 3–41, 2011]. We show that a form of temporal binding by new onsets has to be introduced to the model to simulate the effects of a temporal gap, but that effects of the memory of the old item can stem from continued neural suppression across a temporal gap. We also show that the model can capture the effects of brain lesion on preview search under the different temporal conditions. The study provides a proof-of-principle analysis that neural suppression and temporal binding can be sufficient to account for human search over time and space

Bridging the gap between physiology and behavior: evidence from the sSoTS model of human visual attention

We present the case for a role of biologically plausible neural network modelling in bridging the gap between physiology and behavior. We argue that spiking level networks can allow ‘vertical’ translation between physiological properties of neural systems and emergent ‘whole system’ performance – enabling psychological results to be simulated from implemented networks, and also inferences to be made from simulations concerning processing at a neural level. These models also emphasise particular factors (e.g., the dynamics of performance in relation to real-time neuronal processing) that are not highlighted in other approaches and which can be tested empirically. We illustrate our argument from neural-level models that select stimuli by biased competition. We show that a model with biased competition dynamics can simulate data ranging from physiological studies of single cell activity (Study 1) to ‘whole system’ behavior in human visual search (Study 2), while also capturing effects at ‘intermediate level’, including performance break down after neural lesion (Study 3) and data from brain imaging (Study 4). We also show that, at each level of analysis novel predictions can be derived from the biologically plausible parameters adopted, which we proceed to test (Study 5). We argue that, at least for studying the dynamics of visual attention, the approach productively links single cell to psychological data

Effective Communication for Water Resilient Communities: A Conceptual Framework

Communication campaigns to promote the importance of water as a vital but limited resource have evolved in many ways. Nowadays, the resources, techniques and skills to deliver effective communication campaigns are far greater than ever before. Over the past decades, there has been a significant body of research towards improving water conservation campaign communication but with limited success in promoting more resilient behaviours on behalf of water consumers. While the media and technology have rapidly evolved and awareness among consumers may have increased, this has not been sufficient to make the communication effective in changing behaviour. Communications to promote resilience among consumers need to reach a wide audience, capture audiences’ attention, build awareness and motivate water consumers to consume water sustainably. This represents a subject in need of further theoretical and conceptual investigation. This research reviews various approaches to effective communication and through a synthesis of the concepts aim to present a new, socio-psychological water conservation conceptual framework. The present conceptual framework integrates emotional appeal, for use on social media platforms and in order to foster more water resilient communities. This framework represents a potentially major contribution in providing guidelines for water sectors to deliver effective video communications on social media platform

Previewing distracters reduces their effective contrast

In a visual search task, when half the distracters are presented earlier than the remainder (‘previewed’), observers find the target item more efficiently than when all the items are presented together—the preview benefit. We measured psychometric functions for contrast increments on Gabors that were presented as a valid preview for subsequent search, and when they were a non-predictive (dummy) preview. Sensitivity to contrast increments was lower (rightwards shift of the psychometric function) on valid, compared to dummy previews. This is consistent with an account of the preview benefit in terms of active inhibition, equivalent to lowering the contrast of previewed items that are being actively ignored

Model based analysis of fMRI-data: Applying the sSoTS framework to the neural basic of preview search.

The current work aims to unveil the neural circuits under- lying visual search over time and space by using a model-based analysis of behavioural and fMRI data. It has been suggested by Watson and Humphreys [31] that the prioritization of new stimuli presented in our visual field can be helped by the active ignoring of old items, a process they termed visual marking. Studies using fMRI link the marking pro- cess with activation in superior parietal areas and the precuneus [4, 18, 27, 26]. Marking has been simulated previously using a neural-level ac- count of search, the spiking Search over Time and Space (sSoTS) model, which incorporates inhibitory as well as excitatory mechanisms to guide visual selection. Here we used sSoTS to help decompose the fMRI signals found in a preview search procedure, when participants search for a new target whilst ignoring old distractors. The time course of activity linked to inhibitory and excitatory processes in the model was used as a regres- sor for the fMRI data. The results showed that different neural networks were correlated with top-down excitation and top-down inhibition in the model, enabling us to fractionate brain regions previously linked to vi- sual marking. We discuss the contribution of model-based analysis for decomposing fMRI data

Using biologically plausible neural models to specify the functional and neural mechanisms of visual search

We review research from our laboratory that attempts to pull apart the functional and neural mechanisms of visual search using converging, inter-disciplinary evidence from experimental studies with normal participants, neuropsychological studies with brain lesioned patients, functional brain imaging and computational modelling. The work suggests that search is determined by excitatory mechanisms that support the selection of target stimuli, and inhibitory mechanisms that suppress irrelevant distractors. These mechanisms operate through separable though overlapping neural circuits which can be functionally decomposed by imposing model-based analyses on brain imaging data. The chapter highlights the need for inter-disciplinary research for understanding complex cognitive processes at several levels