The representation of priors and decisions in the human parietal cortex

Animals actively sample their environment through orienting actions such as saccadic eye movements. Saccadic targets are selected based both on sensory evidence immediately preceding the saccade, and a “salience map” or prior built-up over multiple saccades. In the primate cortex, the selection of each individual saccade depends on competition between target-selective cells that ramp up their firing rate to saccade release. However, it is less clear how a cross-saccade prior might be implemented, either in neural firing or through an activity-silent mechanism such as modification of synaptic weights on sensory inputs. Here, we present evidence from magnetoencephalography for 2 distinct processes underlying the selection of the current saccade, and the representation of the prior, in human parietal cortex. While the classic ramping decision process for each saccade was reflected in neural firing rates (measured in the event-related field), a prior built-up over multiple saccades was implemented via modulation of the gain on sensory inputs from the preferred target, as evidenced by rapid frequency tagging. A cascade of computations over time (initial representation of the prior, followed by evidence accumulation and then an integration of prior and evidence) provides a mechanism by which a salience map may be built up across saccades in parietal cortex. It also provides insight into the apparent contradiction that inactivation of parietal cortex has been shown not to affect performance on single-trials, despite the presence of clear evidence accumulation signals in this region

Quantifying decision-making in dynamic, continuously evolving environments

During perceptual decision-making tasks, centroparietal electroencephalographic (EEG) potentials report an evidence accumulation-to-bound process that is time locked to trial onset. However, decisions in real-world environments are rarely confined to discrete trials; they instead unfold continuously, with accumulation of time-varying evidence being recency-weighted towards its immediate past. The neural mechanisms supporting recency-weighted continuous decision-making remain unclear. Here, we use a novel continuous task design to study how the centroparietal positivity (CPP) adapts to different environments that place different constraints on evidence accumulation. We show that adaptations in evidence weighting to these different environments are reflected in changes in the CPP. The CPP becomes more sensitive to fluctuations in sensory evidence when large shifts in evidence are less frequent, and the potential is primarily sensitive to fluctuations in decision-relevant (not decision-irrelevant) sensory input. A complementary triphasic component over occipito-parietal cortex encodes the sum of recently accumulated sensory evidence, and its magnitude covaries with parameters describing how different individuals integrate sensory evidence over time. A computational model based on leaky evidence accumulation suggests that these findings can be accounted for by a shift in decision threshold between different environments, which is also reflected in the magnitude of pre-decision EEG activity. Our findings reveal how adaptations in EEG responses reflect flexibility in evidence accumulation to the statistics of dynamic sensory environments

Learning to look : evaluating the student experience of an interactive image appraisal activity

Introduction: Student radiographers have expressed difficulty in performing image appraisal tasks. The purpose of this study was to investigate the value of a workshop delivered to level 4 undergraduate students. All students completed an image appraisal activity, inputting their appraisal into software that displayed their response alongside an expert opinion. They were asked to identify and discuss any discrepancy. Methods: All Level 4 students participated in an image appraisal workshop and were subsequently invited to take part in a focus group immediately after the activity. Twenty-three students took part in three focus groups (n = 7; n = 8; n = 8). A thematic analysis of transcripts was performed alongside validation from observations during the image appraisal activity. Results: Findings demonstrate that despite teaching and resources being available, students had focused on learning a generic checklist for image appraisal, had not appreciated the application of projection specific criteria and felt underprepared. The use of specific criteria and repetition within the task was considered useful. They identified learning needs and misconceptions through peer discussion and via the expert opinion, highlighting the value of feedback. Students enjoyed the workshop and made suggestions for implementation into the curriculum. Conclusion: Educators must not assume that the provision of resources will result in students developing deep knowledge. Teaching and learning strategies that are task specific are recommended to avoid a surface approach to learning. Time, repetition and appropriate feedback are essential to enable learners to develop competence and confidence for complex visual tasks, such as image appraisal

The Effectiveness of Medical Simulation in Teaching Medical Students Critical Care Medicine: A Systematic Review and Meta-analysis

We aimed to assess effectiveness of simulation for teaching medical students critical care medicine and to assess which simulation methods were most useful. We searched AMED, EMBASE, MEDLINE, ERIC, BEI, AEI, plus bibliographies and citations, to July 2013. Randomised controlled trials comparing effectiveness of simulation with another educational intervention, or no teaching, for teaching medical students critical care medicine were included. Assessments for inclusion, quality and data extraction were duplicated and results synthesised using meta-analysis. We included 22 RCTs (n=1325). Fifteen studies comparing simulation with other teaching found simulation to be more effective (SMD 0.84, 95% CI 0.43 to 1.24; p<0.001; I2 89%). High-fidelity simulation was more effective than low-fidelity and subgrouping supported high-fidelity simulation being more effective than other methods. Simulation improved skill acquisition (SMD 1.01, 95% CI 0.49 to 1.53) but was no better than other teaching in knowledge acquisition (SMD 0.41, 95% CI -0.09 to 0.91)

Low arousing positive affect broadens visual attention and alters the thought-action repertoire while broadened visual attention does not

The Broaden-and-Build Theory states that positive emotions broaden cognition and therefore build personal resources. However, missing theoretical precision regarding the interaction of the cognitive processes involved offers a variety of possible explanations for the mechanisms of broadening and building. In Experiment 1 we tested the causality assumption which states that positive emotions first broaden visual attention which in turn leads to broadened cognition. We examined the effects of a broadened, narrowed or neutral attentional scope of 72 subjects (30 men) on their momentary thought-action repertoire. Results showed that there were no significant differences between groups regarding the breadth or the content of the thought-action repertoire. In Experiment 2 we studied the non-causality hypothesis which assumes a non-causal relationship between cognitive processes. We did so by investigating the effects of negative, neutral, and positive affect on the visual attentional scope of 85 subjects (41 men) in Experiment 2a, as well as on the thought-action repertoire of 85 participants (42 men) in Experiment 2b. Results revealed an attentional broadening effect in Experiment 2a but no differences between groups concerning the breadth of the thought-action repertoire in Experiment 2b. However, a theory driven content analysis showed that positive affect promoted social actions whereas negative affect endorsed resource protecting actions. Thus, our results favor the non-causality assumption. Moreover, results indicate that positive emotions do not target personal resources in general but rather resources associated with social behavior. In conclusion, we argue that the Broaden-and-Build Theory should be refined

Perceptual decision-making under uncertainty in humans

On a daily basis, humans need to make decisions in a complex uncertain world that requires them to adapt their decision strategies to the environmental volatility. In order to make a decision, humans often need to integrate noisy information and combine it with prior experience they learned through previous similar decision situations. This thesis examines how humans form decisions based on noisy information using electroencephalography (EEG), and how they make use of prior expectation in order to guide their decisions using magnetoencephalography (MEG). For both parts, models that capture the different decision-making processes were used to make predictions of human behaviour and underlying neural activity. To study how humans integrate noisy evidence a novel continuous random dot motion task was developed in which signal periods had to be detected in a stream of noisy evidence which, in contrast to previous studies, is controlled by the experimenter. Simulations with a leaky accumulator model predicted that participants should discount past evidence to solve the task. Participant behaviour suggests that they adapted their evidence strategy to the frequency and length of signal periods in the noise in a manner that is consistent with leaky accumulation. A contingent negative variation (CNV) signal measured with EEG suggests that the brain adapted its evidence accumulation process in line with the behavioural results. In addition, a P300-like signal encoded the difference between previous and current evidence sample, scaling with the size of the difference and trial frequency. To study how humans update their prior belief about decision outcomes a different random dot motion task was used in which participants had to integrate evidence within trials but also had to integrate prior expectation over past trial outcomes to inform choice. A Bayesian model was fit to subjects’ behavioural data to estimate the prior expectation on each trial that was subsequently used to study human choice behaviour and neural activity in the task. Human choice behaviour depended on both, the within-trial evidence, as well as prior belief. Activity in parietal cortex, measured with MEG, at the time of feedback suggested that the feedback type, i.e., whether a choice was correct or incorrect, is encoded in parietal cortex. There was only a very weak influence of prior belief on the neural signal. </p