Visual salience of the stop signal affects the neuronal dynamics of controlled inhibition

The voluntary control of movement is often tested by using the countermanding, or stop-signal task that sporadically requires the suppression of a movement in response to an incoming stop-signal. Neurophysiological recordings in monkeys engaged in the countermanding task have shown that dorsal premotor cortex (PMd) is implicated in movement control. An open question is whether and how the perceptual demands inherent the stop-signal affects inhibitory performance and their underlying neuronal correlates. To this aim we recorded multi-unit activity (MUA) from the PMd of two male monkeys performing a countermanding task in which the salience of the stop-signals was modulated. Consistently to what has been observed in humans, we found that less salient stimuli worsened the inhibitory performance. At the neuronal level, these behavioral results were subtended by the following modulations: when the stop-signal was not noticeable compared to the salient condition the preparatory neuronal activity in PMd started to be affected later and with a less sharp dynamic. This neuronal pattern is probably the consequence of a less efficient inhibitory command useful to interrupt the neural dynamic that supports movement generation in PMd

Neural Basis of Social and Perceptual Decision-making in Humans

We make decisions in every moment of our lives. How the brain forms those decisions has been an active topic of inquiry in the field of brain science in recent years. In this dissertation, I discuss our recent neuroimaging studies in trying to uncover the functional architecture of the human brain during social and perceptual decision-making processes. Our decisions in social context vary tremendously with many factors including emotion, reward, social norms, treatments from others, cooperation, and dependence to others. We studied the neural basis of social decision-making processes with a functional magnetic resonance imaging (fMRI) experiment using three economic exchange games with undercompensating, nearly equal, and overcompensating offers. Refusals of undercompensating offers recruited the right dorsolateral prefrontal cortex (dlPFC). Accepting of overcompensating offers recruited the brain reward pathway consisting of the caudate, the cingulate cortex, and the thalamus. Protesting of decisions activated the network consisting of the right dlPFC, the left ventrolateral prefrontal cortex, and midbrain in the substantia nigra. These findings suggested that social decisions are the results of coordination between evaluated fairness norms, self-interest, and reward. In the topic of perceptual decision-making, we contributed to answering how diverse cortical structures are involved in relaying and processing of sensory information to make a sense of environment around us. We conducted two fMRI experiments. In the first experiment, we used an audio-visual (AV) synchrony and asynchrony perceptual categorization task. In the second experiment, we used a face-house categorization task. Stimuli in the second experiment included three levels of noise in face and house images. In AV, we investigated the effective connectivity within the salience network consisting of the anterior insulae and anterior cingulate cortex. In face-house, we discovered that the BOLD activity in the dlPFC, the bidirectional connectivity between the fusiform face area (FFA) and the parahippocampal place area (PPA), and the feedforward connectivity from these regions to the dlPFC increased with the noise level – thus with difficulty of decision-making. These results support that the FFA-PPA-dlPFC network plays an important role for relaying and integrating competing sensory information to arrive at perceptual decisions of face and house

Salience-based selection: attentional capture by distractors less salient than the target

Current accounts of attentional capture predict the most salient stimulus to be invariably selected first. However, existing salience and visual search models assume noise in the map computation or selection process. Consequently, they predict the first selection to be stochastically dependent on salience, implying that attention could even be captured first by the second most salient (instead of the most salient) stimulus in the field. Yet, capture by less salient distractors has not been reported and salience-based selection accounts claim that the distractor has to be more salient in order to capture attention. We tested this prediction using an empirical and modeling approach of the visual search distractor paradigm. For the empirical part, we manipulated salience of target and distractor parametrically and measured reaction time interference when a distractor was present compared to absent. Reaction time interference was strongly correlated with distractor salience relative to the target. Moreover, even distractors less salient than the target captured attention, as measured by reaction time interference and oculomotor capture. In the modeling part, we simulated first selection in the distractor paradigm using behavioral measures of salience and considering the time course of selection including noise. We were able to replicate the result pattern we obtained in the empirical part. We conclude that each salience value follows a specific selection time distribution and attentional capture occurs when the selection time distributions of target and distractor overlap. Hence, selection is stochastic in nature and attentional capture occurs with a certain probability depending on relative salience

Attentive monitoring of multiple video streams driven by a Bayesian foraging strategy

In this paper we shall consider the problem of deploying attention to subsets of the video streams for collating the most relevant data and information of interest related to a given task. We formalize this monitoring problem as a foraging problem. We propose a probabilistic framework to model observer's attentive behavior as the behavior of a forager. The forager, moment to moment, focuses its attention on the most informative stream/camera, detects interesting objects or activities, or switches to a more profitable stream. The approach proposed here is suitable to be exploited for multi-stream video summarization. Meanwhile, it can serve as a preliminary step for more sophisticated video surveillance, e.g. activity and behavior analysis. Experimental results achieved on the UCR Videoweb Activities Dataset, a publicly available dataset, are presented to illustrate the utility of the proposed technique.Comment: Accepted to IEEE Transactions on Image Processin

A review of research into the development of radiologic expertise: Implications for computer-based training

Rationale and Objectives. Studies of radiologic error reveal high levels of variation between radiologists. Although it is known that experts outperform novices, we have only limited knowledge about radiologic expertise and how it is acquired.Materials and Methods. This review identifies three areas of research: studies of the impact of experience and related factors on the accuracy of decision-making; studies of the organization of expert knowledge; and studies of radiologists' perceptual processes.Results and Conclusion. Interpreting evidence from these three paradigms in the light of recent research into perceptual learning and studies of the visual pathway has a number of conclusions for the training of radiologists, particularly for the design of computer-based learning programs that are able to illustrate the similarities and differences between diagnoses, to give access to large numbers of cases and to help identify weaknesses in the way trainees build up a global representation from fixated regions

A review of self-processing biases in cognition

When cues in the environment are associated with self (e.g., one’s own name, face, or coffee cup), these items trigger processing biases such as increased attentional focus, perceptual prioritization and memorial support. This paper reviews the existing literature on self-processing biases before introducing a series of studies that provide new insight into the influence of the self on cognition. In particular, the studies examine affective and memorial biases for self-relevant stimuli, and their flexible application in response to different task demands. We conclude that self-processing biases function to ensure that self-relevant information is attended to and preferentially processed because this is a perpetual goal of the self-system. However, contrary task-demands or priming can have an attenuating effect on their influence, speaking to the complexity and dynamism of the self-processing system in cognition

On the neural origin of pseudoneglect: EEG-correlates of shifts in line bisection performance with manipulation of line length

Healthy participants tend to show systematic biases in spatial attention, usually to the left. However, these biases can shift rightward as a result of a number of experimental manipulations. Using electroencephalography (EEG) and a computerized line bisection task, here we investigated for the first time the neural correlates of changes in spatial attention bias induced by line-length (the so-called line-length effect). In accordance with previous studies, an overall systematic left bias (pseudoneglect) was present during long line but not during short line bisection performance. This effect of line-length on behavioral bias was associated with stronger right parieto-occipital responses to long as compared to short lines in an early time window (100–200 ms) post-stimulus onset. This early differential activation to long as compared to short lines was task-independent (present even in a non-spatial control task not requiring line bisection), suggesting that it reflects a reflexive attentional response to long lines. This was corroborated by further analyses source-localizing the line-length effect to the right temporo-parietal junction (TPJ) and revealing a positive correlation between the strength of this effect and the magnitude by which long lines (relative to short lines) drive a behavioral left bias across individuals. Therefore, stimulus-driven left bisection bias was associated with increased right hemispheric engagement of areas of the ventral attention network. This further substantiates that this network plays a key role in the genesis of spatial bias, and suggests that post-stimulus TPJ-activity at early information processing stages (around the latency of the N1 component) contributes to the left bias

Oscillatory Network Dynamics in Perceptual Decision-Making

Synchronized oscillations of ensembles of neurons in the brain underlie human cognition and behaviors. Neuronal network oscillations can be described by the physics of coupled dynamical systems. This dissertation examines the dynamic network activities in two distinct neurocognitive networks, the salience network (SN) and the ventral temporal cortex-dorsolateral prefrontal cortex (VTC-DLPFC) network, during perceptual decision-making (PDM). The key nodes of the SN include the right anterior insula (rAI), left anterior insula (lAI), and dorsal anterior cingulate cortex (dACC) in the brain. When and how a sensory signal enters and organizes within the SN before reaching the central executive network including the prefrontal cortex has been a mystery. Second, prior studies also report that perception of visual objects (face and house) involves a network of the VTC—the fusiform face area (FFA) and para-hippocampal place area (PPA)—and the DLPFC. How sensory information enters and organizes within the VTC-DLPFC network is not well understood, in milliseconds time-scale of human’s perception and decision-making. We used clear and noisy face/house image categorization tasks and scalp electroencephalography (EEG) recordings to study the dynamics of these networks. We demonstrated that beta (13–30 Hz) oscillation bound the SN, became most active around 100 ms after the stimulus onset, the rAI acted as a main outflow hub within the SN, and the SN activities were negatively correlated with the difficult tasks. We also uncovered that the VTC-DLPFC network activities were mediated by beta (13-30 Hz) and gamma (30-100 Hz) oscillations. Beta activities were enhanced in the time frame 125-250 ms after stimulus onset, the VTC acted as main outflow hub, and network activities were negatively correlated with the difficult tasks. In contrast, gamma activities were elevated in the time frame 0-125 ms, the DLPFC acted as a main outflow hub, and network activities—specifically the FFA-PPA pair—were positively correlated with the difficult tasks. These findings significantly enhance our understanding of how sensory information enters and organizes within the SN and the VTC-DLPFC network, respectively in PDM