133 research outputs found
Are there three subdivisions in the primate subthalamic nucleus?
The prevailing academic opinion holds that the subthalamic nucleus (STN) consists of three parts, each anatomically distinct and selectively associated with cognitive, emotional, or motor functioning. We independently tested this assumption by summarizing the results from 33 studies on STN subdivisions in human and nonhuman primates. The studies were conducted from 1925 to 2010 and feature three different techniques: electrical lesions, anterograde and retrograde tracers, and classical cytoarchitectonics. Our results reveal scant evidence in support of a tripartite STN. Instead, our results show that the variability across studies is surprisingly large, both in the number of subdivisions and in their anatomical localization. We conclude that the number of subdivisions in the STN remains uncertain, and that academic consensus in support of a tripartite STN is presently unwarranted
Self-reported mind wandering reflects executive control and selective attention
Mind wandering is ubiquitous in everyday life and has a pervasive and profound impact on task-related performance. A range
of psychological processes have been proposed to underlie these performance-related decrements, including failures of executive control, volatile information processing, and shortcomings in selective attention to critical task-relevant stimuli. Despite
progress in the development of such theories, existing descriptive analyses have limited capacity to discriminate between
the theories. We propose a cognitive-model based analysis that simultaneously explains self-reported mind wandering and
task performance. We quantitatively compare six explanations of poor performance in the presence of mind wandering. The
competing theories are distinguished by whether there is an impact on executive control and, if so, how executive control acts
on information processing, and whether there is an impact on volatility of information processing. Across two experiments
using the sustained attention to response task, we fnd quantitative evidence that mind wandering is associated with two
latent factors. Our strongest conclusion is that executive control is impaired: increased mind wandering is associated with
reduced ability to inhibit habitual response tendencies. Our nuanced conclusion is that executive control defcits manifest in
reduced ability to selectively attend to the information value of rare but task-critical events
Toward a model-based cognitive neuroscience of mind wandering
Published version also available at http://dx.doi.org/10.1016/j.neuroscience.2015.09.053People often ‘‘mind wander” during everyday
tasks, temporarily losing track of time, place, or current task
goals. In laboratory-based tasks, mind wandering is often
associated with performance decrements in behavioral
variables and changes in neural recordings. Such empirical
associations provide descriptive accounts of mind
wandering – howit affects ongoing task performance – but fail
to provide true explanatory accounts – why it affects task
performance. In this perspectives paper, we consider mind
wandering as a neural state or process that affects the
parameters of quantitative cognitive process models, which
in turn affect observed behavioral performance. Our
approach thus uses cognitive process models to bridge
the explanatory divide between neural and behavioral data.
We provide an overview of two general frameworks for
developing a model-based cognitive neuroscience of mind
wandering. The first approach uses neural data to segment
observed performance into a discrete mixture of latent
task-related and task-unrelated states, and the second
regresses single-trial measures of neural activity onto
structured trial-by-trial variation in the parameters of
cognitive process models. We discuss the relative merits of
the two approaches, and the research questions they can
answer, and highlight that both approaches allow neural data
to provide additional constraint on the parameters of cognitive
models, which will lead to a more precise account of the
effect of mind wandering on brain and behavior. We conclude
by summarizing prospects for mind wandering as conceived
within a model-based cognitive neuroscience framework,
highlighting the opportunities for its continued study and
the benefits that arise from using well-developed quantitative techniques to study abstract theoretical constructs
Do We Need a Human post mortem Whole-Brain Anatomical Ground Truth in in vivo Magnetic Resonance Imaging?
Non-invasive in vivo neuroimaging techniques provide a wide array of possibilities to study human brain function. A number of approaches are available that improve our understanding of the anatomical location of brain activation patterns, including the development of probabilistic conversion tools to register individual in vivo data to population based neuroanatomical templates. Two elegant examples were published by Horn et al. (2017) in which a method was described to warp DBS electrode coordinates, and histological data to MNI-space (Ewert et al., 2017). The conversion of individual brain scans to a standard space is done assuming that individual anatomical scans provide a reliable image of the underlying neuroanatomy. It is unclear to what extent spatial distortions related to tissue properties, or MRI artifacts exist in these scans. Therefore, the question rises whether the anatomical information from the individual scans can be considered a real ground truth. To accommodate the knowledge-gap as a result of limited anatomical information, generative brain models have been developed circumventing these challenges through the application of assumption sets without recourse to any ground truth. We would like to argue that, although these efforts are valuable, the definition of an anatomical ground truth is preferred. Its definition requires a system in which non-invasive approaches can be validated using invasive methods of investigation. We argue that the application of post mortem MRI studies in combination with microscopy analyses brings an anatomical ground truth for the human brain within reach, which is of importance for all research within the human in vivo neuroimaging field
Individual Differences in Heart Rate Variability Predict the Degree of Slowing during Response Inhibition and Initiation in the Presence of Emotional Stimuli
Response inhibition is a hallmark of executive control and crucial to support flexible behavior in a constantly changing environment. Recently, it has been shown that response inhibition is influenced by the presentation of emotional stimuli (Verbruggen and De Houwer, 2007). Healthy individuals typically differ in the degree to which they are able to regulate their emotional state, but it remains unknown whether individual differences in emotion regulation (ER) may alter the interplay between emotion and response inhibition. Here we address this issue by testing healthy volunteers who were equally divided in groups with high and low heart rate variability (HRV) during rest, a physiological measure that serves as proxy of ER. Both groups performed an emotional stop-signal task, in which negative high arousing pictures served as negative emotional stimuli and neutral low arousing pictures served as neutral non-emotional stimuli. We found that individuals with high HRV activated and inhibited their responses faster compared to individuals with low HRV, but only in the presence of negative stimuli. No group differences emerged for the neutral stimuli. Thus, individuals with low HRV are more susceptible to the adverse effects of negative emotion on response initiation and inhibition. The present research corroborates the idea that the presentation of emotional stimuli may interfere with inhibition and it also adds to previous research by demonstrating that the aforementioned relationship varies for individuals differing in HRV. We suggest that focusing on individual differences in HRV and its associative ER may shed more light on the dynamic interplay between emotion and cognition
The impact of MRI scanner environment on perceptual decision-making
Despite the widespread use of functional magnetic resonance imaging (fMRI), few studies have addressed scanner effects on performance. The studies that have examined this question show a wide variety of results. In this article we report analyses of three experiments in which participants performed a perceptual decision-making task both in a traditional setting as well as inside an MRI scanner. The results consistently show that response times increase inside the scanner. Error rates also increase, but to a lesser extent. To reveal the underlying mechanisms that drive the behavioral changes when performing a task inside the MRI scanner, the data were analyzed using the linear ballistic accumulator model of decision-making. These analyses show that, in the scanner, participants exhibit a slow down of the motor component of the response and have less attentional focus on the task. However, the balance between focus and motor slowing depends on the specific task requirements
Piéron’s Law and Optimal Behavior in Perceptual Decision-Making
Piéron’s Law is a psychophysical regularity in signal detection tasks that states that mean response times decrease as a power function of stimulus intensity. In this article, we extend Piéron’s Law to perceptual two-choice decision-making tasks, and demonstrate that the law holds as the discriminability between two competing choices is manipulated, even though the stimulus intensity remains constant. This result is consistent with predictions from a Bayesian ideal observer model. The model assumes that in order to respond optimally in a two-choice decision-making task, participants continually update the posterior probability of each response alternative, until the probability of one alternative crosses a criterion value. In addition to predictions for two-choice decision-making tasks, we extend the ideal observer model to predict Piéron’s Law in signal detection tasks. We conclude that Piéron’s Law is a general phenomenon that may be caused by optimality constraints
Advance Preparation in Task-Switching: Converging Evidence from Behavioral, Brain Activation, and Model-Based Approaches
Recent research has taken advantage of the temporal and spatial resolution of event-related brain potentials (ERPs) and functional magnetic resonance imaging (fMRI) to identify the time course and neural circuitry of preparatory processes required to switch between different tasks. Here we overview some key findings contributing to understanding strategic processes in advance preparation. Findings from these methodologies are compatible with advance preparation conceptualized as a set of processes activated for both switch and repeat trials, but with substantial variability as a function of individual differences and task requirements. We then highlight new approaches that attempt to capitalize on this variability to link behavior and brain activation patterns. One approach examines correlations among behavioral, ERP and fMRI measures. A second “model-based” approach accounts for differences in preparatory processes by estimating quantitative model parameters that reflect latent psychological processes. We argue that integration of behavioral and neuroscientific methodologies is key to understanding the complex nature of advance preparation in task-switching
Revisiting the Evidence for Collapsing Boundaries and Urgency Signals in Perceptual Decision-Making
For nearly 50 years, the dominant account of decision-making holds that noisy information is accumulated until a fixed threshold is crossed. This account has been tested extensively against behavioral and neurophysiological data for decisions about consumer goods, perceptual stimuli, eyewitness testimony, memories, and dozens of other paradigms, with no systematic misfit between model and data. Recently, the standard model has been challenged by alternative accounts that assume that less evidence is required to trigger a decision as time passes. Such "collapsing boundaries" or "urgency signals" have gained popularity in some theoretical accounts of neurophysiology. Nevertheless, evidence in favor of these models is mixed, with support coming from only a narrow range of decision paradigms compared with a long history of support from dozens of paradigms for the standard theory. We conducted the first large-scale analysis of data from humans and nonhuman primates across three distinct paradigms using powerful model-selection methods to compare evidence for fixed versus collapsing bounds. Overall, we identified evidence in favor of the standard model with fixed decision boundaries. We further found that evidence for static or dynamic response boundaries may depend on specific paradigms or procedures, such as the extent of task practice. We conclude that the difficulty of selecting between collapsing and fixed bounds models has received insufficient attention in previous research, calling into question some previous results
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