Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms “method” and “method bias” and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.

Sources of Method Bias in Social Science Research and Recommendations on How to Control It

The majority of functional neuroscience studies have focused on the brain's response to a task or stimulus. However, the brain is very active even in the absence of explicit input or output. In this Article we review recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity. Although several challenges remain, these studies have provided insight into the intrinsic functional architecture of the brain, variability in behaviour and potential physiological correlates of neurological and psychiatric disease.

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Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging.

The Reorienting System of the Human Brain: From Environment to Theory of Mind

A fundamental challenge for systems neuroscience is to quantitatively relate its three major branches of research: brain-activity measurement, behavioral measurement, and computational modeling. Using measured brain-activity patterns to evaluate computational network models is complicated by the need to define the correspondency between the units of the model and the channels of the brain-activity data, e.g. single-cell recordings or voxels from functional magnetic resonance imaging (fMRI). Similar correspondency problems complicate relating activity patterns between different modalities of brain-activity measurement, and between subjects and species. In order to bridge these divides, we suggest abstracting from the activity patterns themselves and computing representational dissimilarity matrices, which characterize the information carried by a given representation in a brain or model. We propose a new experimental and data-analytical framework called representational similarity analysis (RSA), in which multi-channel measures of neural activity are quantitatively related to each other and to computational theory and behavior by comparing representational dissimilarity matrices. We demonstrate RSA by relating representations of visual objects as measured with fMRI to computational models spanning a wide range of complexities. We argue that these ideas, which have deep roots in psychology and neuroscience, will allow the integrated quantitative analysis of data from all three branches, thus contributing to a more unified systems neuroscience.

https://www.mrc-cbu.cam.ac.uk/wp-content/uploads/2013/01/kriegeskorte_RSA_frontiersSN20081.pdf

Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience

Fate of unattended fearful faces in the amygdala is determined by both attentional resources and cognitive modulation

How does motivation interact with cognitive control during challenging behavioral conditions? Here, we investigated the interactions between motivation and cognition during a response conflict task and tested a specific model of the effect of reward on cognitive processing. Behaviorally, participants exhibited reduced conflict during the reward versus no-reward condition. Brain imaging results revealed that a group of subcortical and fronto-parietal regions was robustly influenced by reward at cue processing and, importantly, that cue-related responses in fronto-parietal attentional regions were predictive of reduced conflict-related signals in the medial pFC (MPFC)/ACC during the upcoming target phase. Path analysis revealed that the relationship between cue responses in the right intraparietal sulcus (IPS) and interference-related responses in the MPFC during the subsequent target phase was mediated via signals in the left fusiform gyrus, which we linked to distractor-related processing. Finally, reward increased functional connectivity between the right IPS and both bilateral putamen and bilateral nucleus accumbens during the cue phase, a relationship that covaried with across-individual sensitivity to reward in the case of the right nucleus accumbens. Taken together, our findings are consistent with a model in which motivationally salient cues are employed to upregulate top-down control processes that bias the selection of visual information, thereby leading to more efficient stimulus processing during conflict conditions.

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Reward reduces conflict by enhancing attentional control and biasing visual cortical processing

We investigated how the brain integrates motivational and attentional signals by using a neuroimaging paradigm that provided separate estimates for transient cue- and target-related signals, in addition to sustained block-related responses. Participants performed a Posner-type task in which an endogenous cue predicted target location on 70% of trials, while motivation was manipulated by varying magnitude and valence of a cash incentive linked to task performance. Our findings revealed increased detection performance (d′) as a function of incentive value. In parallel, brain signals revealed that increases in absolute incentive magnitude led to cue- and target-specific response modulations that were independent of sustained state effects across visual cortex, fronto-parietal regions, and subcortical regions. Interestingly, state-like effects of incentive were observed in several of these brain regions, too, suggesting that both transient and sustained fMRI signals may contribute to task performance. For both cue and block periods, the effects of administering incentives were correlated with individual trait measures of reward sensitivity. Taken together, our findings support the notion that motivation improves behavioral performance in a demanding attention task by enhancing evoked responses across a distributed set of anatomical sites, many of which have been previously implicated in attentional processing. However, the effect of motivation was not simply additive as the impact of absolute incentive was greater during invalid than valid trials in several brain regions, possibly because motivation had a larger effect on reorienting than orienting attentional mechanisms at these sites.

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Combined effects of attention and motivation on visual task performance: transient and sustained motivational effects

Cognition and emotion interact to determine ongoing behaviors. In this study, we investigated the interaction between cognition and emotion during response inhibition using the stop-signal task. In Experiment 1, low-threat stop-signals comprising fearful and happy face pictures were employed. We found that both fearful and happy faces improved response inhibition relative to neutral ones. In Experiment 2, we employed high-threat emotional stimuli as stop signals, namely stimuli previously paired with mild shock. In this case, inhibitory performance was impaired relative to a neutral condition. We interpret these findings in terms of the impact of emotional stimuli on early sensory/attentional processing, which resulted in improved performance (Experiment 1), and in terms of their impact at more central stages, which impaired performance (Experiment 2). Taken together, our findings demonstrate that emotion can either enhance or impair cognitive performance depending on the emotional potency of the stimuli involved.

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Srikanth Padmala

Papers

Fate of unattended fearful faces in the amygdala is determined by both attentional resources and cognitive modulation

Reward reduces conflict by enhancing attentional control and biasing visual cortical processing

Combined effects of attention and motivation on visual task performance: transient and sustained motivational effects

Interactions between cognition and emotion during response inhibition.

Interactions between cognition and motivation during response inhibition