Punishing an error improves learning: The influence of punishment magnitude on error-related neural activity and subsequent learning

Punishing an error to shape subsequent performance is a major tenet of individual and societal level behavioral interventions. Recent work examining error-related neural activity has identified that the magnitude of activity in the posterior medial frontal cortex (pMFC) is predictive of learning from an error, whereby greater activity in this region predicts adaptive changes in future cognitive performance. It remains unclear how punishment influences error-related neural mechanisms to effect behavior change, particularly in key regions such as pMFC, which previous work has demonstrated to be insensitive to punishment. Using an associative learning task that provided monetary reward and punishment for recall performance, we observed that when recall errors were categorized by subsequent performance— whether the failure to accurately recall a number–location association was corrected at the next presentation of the same trial—the magnitude of error-related pMFC activity predicted future correction. However, the pMFC region was insensitive to the magnitude of punishment an error received and it was the left insula cortex that predicted learning from the most aversive outcomes. These findings add further evidence to the hypothesis that error-related pMFC activity may reflect more than a prediction error in representing the value of an outcome. The novel role identified here for the insular cortex in learning from punishment appears particularly compelling for our understanding of psychiatric and neurologic conditions that feature both insular cortex dysfunction and a diminished capacity for learning from negative feedback or punishment. Copyright©2010 the author

Short-Term Memory Maintenance of Object Locations during Active Navigation: Which Working Memory Subsystem Is Essential?

The goal of the present study was to examine the extent to which working memory supports the maintenance of object locations during active spatial navigation. Participants were required to navigate a virtual environment and to encode the location of a target object. In the subsequent maintenance period they performed one of three secondary tasks that were designed to selectively load visual, verbal or spatial working memory subsystems. Thereafter participants re-entered the environment and navigated back to the remembered location of the target. We found that while navigation performance in participants with high navigational ability was impaired only by the spatial secondary task, navigation performance in participants with poor navigational ability was impaired equally by spatial and verbal secondary tasks. The visual secondary task had no effect on navigation performance. Our results extend current knowledge by showing that the differential engagement of working memory subsystems is determined by navigational ability

Mean absolute metric error (±1 standard error) for the poor navigators, plotted separately for the three different secondary task conditions and the control condition (without interference).

<p>Mean absolute metric error (±1 standard error) for the poor navigators, plotted separately for the three different secondary task conditions and the control condition (without interference).</p

Schematic of the virtual environment used in the navigation task.

<p>(a) Example display of the virtual environment during the encoding phase of an experimental trial. Landmarks are shown in red, green and blue. The target is shown in yellow, with a virtual light beacon projecting vertically from its apex. (b) Sequence of events in a typical experimental trial. Participants entered the environment and navigated to the target before pressing a button on the joystick to indicate when they reached its location. The encoding phase was followed by a delay period (11 seconds), in which participants were asked simply to remember the object's location (control task), or they were asked to perform one of three secondary tasks (visual, verbal or spatial). In the subsequent retrieval phase, participants re-entered the arena from a different location than in the encoding phase (shifted by 90°, 180° or 270°, with equal probability). They were required to navigate to the location of the target, which was now absent from the display, and to indicate via the joystick when they had arrived there. The next trial commenced after a further delay of 3 seconds.</p

Selective estrogen receptor modulation increases hippocampal activity during probabilistic association learning in schizophrenia

People with schizophrenia show probabilistic association learning impairment in conjunction with abnormal neural activity. The selective estrogen receptor modulator (SERM) raloxifene preserves neural activity during memory in healthy older men and improves memory in schizophrenia. Here, we tested the extent to which raloxifene modifies neural activity during learning in schizophrenia. Nineteen people with schizophrenia participated in a twelve-week randomized, double-blind, placebo-controlled, cross-over adjunctive treatment trial of the SERM raloxifene administered orally at 120 mg daily to assess brain activity during probabilistic association learning using functional magnetic resonance imaging (fMRI). Raloxifene improved probabilistic association learning and significantly increased fMRI BOLD activity in the hippocampus and parahippocampal gyrus relative to placebo. A separate region of interest confirmatory analysis in 21 patients vs 36 healthy controls showed a positive association between parahippocampal neural activity and learning in patients, but no such relationship in the parahippocampal gyrus of healthy controls. Thus, selective estrogen receptor modulation by raloxifene concurrently increases activity in the parahippocampal gyrus and improves probabilistic association learning in schizophrenia. These results support a role for estrogen receptor modulation of mesial temporal lobe neural activity in the remediation of learning disabilities in both men and women with schizophrenia

Results from the ROI analyses: (1) the main effect of the emotional go/no-go task, contrasting the inhibition of responses to negative stimuli with the inhibition of responses to neutral stimuli (“inhibit negative vs. neutral”) and (2) for the regression analysis of serum testosterone levels on BOLD response for the same contrast.

<p>Separate analyses were conducted in the men with schizophrenia and the healthy men.</p><p><i>Note: *Indicates the effect survived FDR correction for multiple comparisons.</i></p

Demographic and clinical characteristics of the sample, comprising 18 males with schizophrenia and 22 healthy males.

<p>Means are listed, with standard deviations in parentheses.</p

Results of a regression analysis in the men with schizophrenia and healthy men showing scatter plots of significant inverse correlations between testosterone levels and BOLD response in the bilateral middle frontal gyrus ROIs and the left insula ROIs for the inhibit negative versus neutral contrast in men with schizophrenia and no relationship in healthy men.

<p>Results of a regression analysis in the men with schizophrenia and healthy men showing scatter plots of significant inverse correlations between testosterone levels and BOLD response in the bilateral middle frontal gyrus ROIs and the left insula ROIs for the inhibit negative versus neutral contrast in men with schizophrenia and no relationship in healthy men.</p

A whole-brain rendered image in the healthy men, showing significantly increased BOLD response when contrasting the inhibit negative and the inhibit neutral task conditions, p = .001 uncorrected with a minimum voxel extent k≥18.

<p>The healthy men showed a network of increased activation that overlapped with previous findings (Vercammen et al., 2012, <i>Journal of Psychiatry and Neuroscience,37(6): 379–388</i>). We applied the statistical criterion employed previously with this paradigm (Vercammen et al., 2012, <i>Journal of Psychiatric Research</i>), based on a double threshold approach. A simulation script was used to determine cluster threshold (cluster_threshold_beta.m retrieved from <a href="https://www2.bc.edu/~slotnics/scripts.htm" target="_blank">https://www2.bc.edu/~slotnics/scripts.htm</a>), with the following parameters: acquisition matrix (80×80), original voxel dimensions (3×3×3), number of slices (32), full width half maximum (FWHM) set to 0, resampled voxel resolution (2×2×2), mask (none), corrected p-value (.05), voxel based p-value (.001), iterations (1000).</p

Group means and standard deviations for behavioural performance parameters on the emotional Go/No-Go task.

<p><i>Note: Reaction times refer to correct responses only. Accuracy reflects both responses to targets and withheld responses to distracters. False alarm errors indicate responses to distracters. Omissions indicate withheld responses to targets.</i></p