Investigating Intra-Individual Networks of Response Inhibition and Interference Resolution using 7T MRI

Response inhibition and interference resolution are often considered subcomponents of an overarching inhibition system that utilizes the so-called cortico-basal-ganglia loop. Up until now, most previous functional magnetic resonance imaging (fMRI) literature has compared the two using between-subject designs, pooling data in the form of a meta-analysis or comparing different groups. Here, we investigate the overlap of activation patterns underlying response inhibition and interference resolution on a within-subject level, using ultra-high field MRI. In this model-based study, we furthered the functional analysis with cognitive modelling techniques to provide a more in-depth understanding of behaviour. We applied the stop-signal task and multi-source interference task to measure response inhibition and interference resolution, respectively. Our results lead us to conclude that these constructs are rooted in anatomically distinct brain areas and provide little evidence for spatial overlap. Across the two tasks, common BOLD responses were observed in the inferior frontal gyrus and anterior insula. Interference resolution relied more heavily on subcortical components, specifically nodes of the commonly referred to indirect and hyperdirect pathways, as well as the anterior cingulate cortex, and pre-supplementary motor area. Our data indicated that orbitofrontal cortex activation is specific to response inhibition. Our model-based approach provided evidence for the dissimilarity in behavioural dynamics between the two tasks. The current work exemplifies the importance of reducing inter-individual variance when comparing network patterns and the value of UHF-MRI for high resolution functional mapping.

Beyond curve fitting? Comment on Liu, Mayer-Kress, and Newell (2003)

Y.-T. Liu, G. Mayer-Kress, and K. M. Newell (2003) fit learning curves to movement time data and suggested 2 new methods for analyzing learning. They claimed that the methods go "beyond curve fitting." However, in neither their curve fitting nor their new methods is measurement noise accounted for, and therefore they produce inefficient and biased results. Using the data of Liu et al., in which variance caused by learning is small relative to the level of noise for most participants, the present authors demonstrate those problems and provide better alternatives that are more noise tolerant, more powerful, and go beyond curve fitting without displaying the extreme bias produced by the methods of Liu et al.

Response-time dynamics: evidence for linear and low-dimensional nonlinear structure in human choice sequences

Response time (RT) is a commonly used measure of cognitive performance, which is usually characterized as stochastic. However, useful information may be hidden in the apparently random fluctuations of RT. Dynamical systems analysis techniques allow an exploration of the alternative hypothesis that RT fluctuations are deterministic, albeit in a complex manner. We applied careful task construction and noise-reduction and surrogate series tests to show that RT series from a forced-pace serial response-time task have low-dimensional chaotic characteristics. In Experiment 1, 80% of subjects' filtered RT series had low dimensionality, sensitive dependence on initial conditions, spectra close to 1/f, and stable attractor geometry across sessions. In Experiment 2, we showed that the size of the inter-stimulus interval (ISI) determined the number of subjects with low-dimensional chaotic series. A small ISI caused 100% of subjects to respond in the chaotic regime, whereas only 25% had a low-dimensional chaotic RT component when the ISI was large. We argue that demanding task requirements cause a reduction in the dimensionality of the dynamics, producing RT fluctuations that may reflect a response strategy for controlling RT.

A nonlinear regression approach to estimating signal detection models for rating data

This paper considers a regression approach to estimating signal detection parameters for rating data. The methodology is based on the statistical modeling of ordinal data and requires only standard statistical software such as SAS (SAS/STAT User's Guide, 1999) for computation. The approach is more efficient than the current practice of extracting the parameter estimates with the use of specialized software and analyzing the estimates with the use of a standard statistical package. It greatly facilitates exploration of the effects of covariates on model parameters. The method is illustrated using a published data set from a single factor multiple-alternative perceptual task, and data from a more complex factorial design examining recognition memory rating data.

Distinguishing common and task-specific processes in word identification: a matter of some moment?

The same 500 words were presented in 6 different word identification tasks (Experiment 1: lexical decision, semantic categorization, and 3 speeded naming tasks; Experiment 2: delayed naming). Reaction time (RT) distributions were estimated for each task and analyses tested for the effects of word frequency and animacy on various parameters of the RT distribution. Low frequency words yielded more skewed distributions than high frequency words in all tasks except delayed naming. The differential skew was most marked for tasks that required lexical discrimination. The semantic categorization task yielded highly skewed distributions for all words, but the word frequency effect was due to shifts in the location of the RT distributions rather than changes in skew. The results are used to evaluate the relative contributions of a common lexical access process and task-specific processes to performance in lexical discrimination and naming tasks.

Factors affecting progress of Australian and international students in a problem-based learning medical course

CONTEXT

Research on the factors affecting progress in medical schools has typically focused on mainstream (non-Indigenous Australian, non-international) students in traditional, didactic programmes. These results may not be applicable to students, particularly those from culturally diverse backgrounds, undertaking problem-based learning courses.

OBJECTIVE

This study used qualitative methodology to explore and compare factors affecting progress for mainstream Australian students (non-Indigenous Australian, non-international) and international students (full fee-paying students who had relocated countries to study) in a problem-based learning medical course. Intervention strategies were devised on the basis of the participants' experiences.

METHODS

Six focus group discussions were conducted (three with mainstream Australian and three with international participants). Transcripts of these discussions were coded and analysed independently by two researchers and discussed until consensus was attained.

RESULTS

Participants identified both positive and negative experiences related to the course structure, which were consistent with previous findings. The participants' experiences demonstrated a relationship between sense of 'belongingness' to the medical school community, participation in learning opportunities and progress through the course.

CONCLUSIONS

The results suggest that interventions aimed at reducing barriers to progress need to promote students' confidence, motivation and subsequent participation in course learning opportunities. These results have application to other problem-based learning courses particularly those which face the challenge of providing an optimal learning environment for students from diverse backgrounds.

The power law repealed: the case for an exponential law of practice

The power function is treated as the law relating response time to practice trials. However, the evidence for a power law is flawed, because it is based on averaged data. We report a survey that assessed the form of the practice function for individual learners and learning conditions in paradigms that have shaped theories of skill acquisition. We fit power and exponential functions to 40 sets of data representing 7,910 learning series from 475 subjects in 24 experiments. The exponential function fit better than the power function in all the unaveraged data sets. Averaging produced a bias in favor of the power function. A new practice function based on the exponential, the APEX function, fit better than a power function with an extra, preexperimental practice parameter. Clearly, the best candidate for the law of practice is the exponential or APEX function, not the generally accepted power function. The theoretical implications are discussed.

Do junior doctors feel they are prepared for hospital practice? A study of graduates from traditional and non-traditional medical schools

A valid and reliable questionnaire was developed which assesses eight subscales relating to key areas of medical hospital-based work. This was used to evaluate junior doctors' perceptions of the adequacy of their undergraduate medical training to prepare them for hospital practice. Data from 139 (60%) first-year doctors (interns) showed that graduates from the problem-based medical school rated their undergraduate preparation more highly than traditional medical school graduates in preparing them for practice in the areas of interpersonal skills, confidence, collaboration with other health care workers, preventive care, holistic care and self-directed learning. These findings persisted when ratings were adjusted for the effects of age and gender. There were no differences between the intern groups for patient management and understanding science. This research suggests that educational experiences in different undergraduate medical courses are important in preparing doctors for their early working life.

Representation and selection of relative position

Part 1 concerns representation: We demonstrate pop-out for a target that can be distinguished from the distractors only by the relative position of its components and thereby show that simple shape information is represented preattentively. We discuss our findings in terms of theories of search and texture segregation. Part 2 concerns selection: We demonstrate strong learning in a varied-mapping paradigm and show that preattentive shape information can be used for selection. Finally, we suggest an account fo the learning, namely the group scale hypothesis, and present a final experiment to test it. Our results confirm and extend the emphasis placed by Duncan and Humphreys' (1989) attentional engagement theory on grouping processes in visual search.

Representation and selection of relative position

Part 1 concerns representation: We demonstrate pop-out for a target that can be distinguished from the distractors only by the relative position of its components and thereby show that simple shape information is represented preattentively. We discuss our findings in terms of theories of search and texture segregation. Part 2 concerns selection: We demonstrate strong learning in a varied-mapping paradigm and show that preattentive shape information can be used for selection. Finally, we suggest an account fo the learning, namely the group scale hypothesis, and present a final experiment to test it. Our results confirm and extend the emphasis placed by Duncan and Humphreys' (1989) attentional engagement theory on grouping processes in visual search.

Response time distributions and the Stroop Task: a test of the Cohen, Dunbar, and McClelland (1990) model

Cohen, Dunbar, and McClelland's (1990) model was tested for Strooplike interference tasks by studying the shape of the distribution of response latencies produced by Ss and by the model. The model correctly anticipates changes in mean response latency (M(RT)) across congruent and incongruent conditions. It does not, however, correctly anticipate changes in the shape of the distributions, even though changes in the shape of the distributions underlie the changes in M(RT). Thus the model predicts M(RT) successfully but for the wrong reason. It is concluded that the model is not an adequate account of Ss' performance in the Stroop task.

Response time distributions and the Stroop task: A test of the Cohen, Dunbar, and McClelland (1990) model

Cohen, Dunbar, and McClelland's (1990) model was tested for Strooplike interference tasks by studying the shape of the distribution of response latencies produced by Ss and by the model. The model correctly anticipates changes in mean response latency (M(RT)) across congruent and incongruent conditions. It does not, however, correctly anticipate changes in the shape of the distributions, even though changes in the shape of the distributions underlie the changes in M(RT). Thus the model predicts M(RT) successfully but for the wrong reason. It is concluded that the model is not an adequate account of Ss' performance in the Stroop task.