Statistical and perceptual updating: correlated impairments in right brain injury

Plinko: Eliciting beliefs to build better models of statistical learning and mental model updating

Prior beliefs are central to Bayesian accounts of cognition, but many of these accounts do not directly measure priors. More specifically, initial states of belief heavily influence how new information is assumed to be utilized when updating a particular model. Despite this, prior and posterior beliefs are either inferred from sequential participant actions or elicited through impoverished means. We had participants to play a version of the game 'Plinko', to first elicit individual participant priors in a theoretically agnostic manner. Subsequent learning and updating of participant beliefs was then directly measured. We show that participants hold various priors that cluster around prototypical probability distributions that in turn influence learning. In follow-up studies, we show that participant priors are stable over time and that the ability to update beliefs is influenced by a simple environmental manipulation (i.e., a short break). These data reveal the importance of directly measuring participant beliefs rather than assuming or inferring them as has been widely done in the literature to date. The Plinko game provides a flexible and fecund means for examining statistical learning and mental model updating.

Lesions to different regions of frontal cortex have dissociable effects on voluntary persistence

Deciding how long to keep waiting for uncertain future rewards is a complex problem. Previous research has shown that choosing to stop waiting results from an evaluative process that weighs the subjective value of the awaited reward against the opportunity cost of waiting. In functional neuroimaging data, activity in ventromedial prefrontal cortex (vmPFC) tracks the dynamics of this evaluation, while activation in the dorsomedial prefrontal cortex (dmPFC) and anterior insula (AI) ramps up before a decision to quit is made. Here, we provide causal evidence of the necessity of these brain regions for successful performance in a willingness-to-wait task. 28 participants with frontal lobe lesions were tested on their ability to adaptively calibrate how long they waited for monetary rewards. We grouped the participants based on the location of their lesions, which were primarily in ventromedial, dorsomedial, or lateral parts of their prefrontal cortex (vmPFC, dmPFC, and lPFC, respectively), or in the anterior insula. We compared the performance of each subset of lesion participants to behavior in a control group without lesions (n=18). Finally, we fit a newly developed computational model to the data to glean a more mechanistic understanding of how lesions affect the cognitive processes underlying choice. We found that participants with lesions to the vmPFC waited less overall, while participants with lesions to the dmPFC and anterior insula were specifically impaired at calibrating their level of persistence to the environment. These behavioral effects were accounted for by systematic differences in parameter estimates from a computational model of task performance: while the vmPFC group showed reduced initial willingness to wait, lesions to the dmPFC/anterior insula were associated with slower learning from negative feedback. These findings corroborate the notion that failures of persistence can be driven by sophisticated cost-benefit analyses rather than lapses in self-control. They also support the functional specialization of different parts of the prefrontal cortex in service of voluntary persistence.

The relative importance of local contingencies and global biases for statistical learning

Effective behavior requires adapting to the changing regularities evident in the world. Analogous to the global and local processing distinction for perception, these statistical regularities may be evident in global biases (i.e., some events are more likely) or local contingencies (i.e., subsequent events depend on preceding events). To explore whether mental model updating unfolds in distinct ways according to global and local statistical properties, we had healthy individuals perform two variations of an updating task in which both global and local statistical properties changed over time. Participants predicted whether the next triangle in a sequence of triangles would point up or down. The probability of pointing up or down was fixed for epochs of trials (i.e., global probability) and correlated with the colors of elements in the display. In addition, we made the triangle's apex direction on trial n+1 depend on the pointing direction of the prior trial (i.e., local probability). For both experiments, it was the local contingencies that dominated participant choices. When global and local statistical cues of equal magnitude are available, we conclude that healthy individuals are biased towards using the local statistical properties.

Formalizing Opponent Modeling with the Rock, Paper, Scissors Game

In simple dyadic games such as rock, paper, scissors (RPS), people exhibit peculiar sequential dependencies across repeated interactions with a stable opponent. These regularities seem to arise from a mutually adversarial process of trying to outwit their opponent. What underlies this process, and what are its limits? Here, we offer a novel framework for formally describing and quantifying human adversarial reasoning in the rock, paper, scissors game. We first show that this framework enables a precise characterization of the complexity of patterned behaviors that people exhibit themselves, and appear to exploit in others. This combination allows for a quantitative understanding of human opponent modeling abilities. We apply these tools to an experiment in which people played 300 rounds of RPS in stable dyads. We find that although people exhibit very complex move dependencies, they cannot exploit these dependencies in their opponents, indicating a fundamental limitation in people’s capacity for adversarial reasoning. Taken together, the results presented here show how the rock, paper, scissors game allows for precise formalization of human adaptive reasoning abilities.

Lateralization, functional specialization, and dysfunction of attentional networks

The present review covers the latest findings on the lateralization of the dorsal and ventral attention systems, their functional specialization, and their clinical relevance for stroke-induced attentional dysfunction. First, the original assumption of a bilateral dorsal system for top-down attention and a right-lateralized ventral system for stimulus-driven attention is critically reviewed. The evidence for the involvement of the left parietal cortex in attentional functions is discussed and findings on putative pathways linking the dorsal and ventral network are presented. In the second part of the review, we focus on the different attentional subsystems and their lateralization, discussing the differences between spatial, feature- and object-based attention, and motor attention. We also review studies based on predictive coding frameworks of attentional functions. Finally, in the third section, we provide an overview of the consequences of specific disruption within the attention networks after stroke. The role of the interhemispheric (im)balance is discussed, and the results of new promising therapeutic approaches employing brain stimulation techniques such as transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS) are presented.

Attentional reorientation along the meridians of the visual field: Are there different neural mechanisms at play?

Hemispatial neglect, after unilateral lesions to parietal brain areas, is characterized by an inability to respond to unexpected stimuli in contralesional space. As the visual field's horizontal meridian is most severely affected, the brain networks controlling visuospatial processes might be tuned explicitly to this axis. We investigated such a potential directional tuning in the dorsal and ventral frontoparietal attention networks, with a particular focus on attentional reorientation. We used an orientation‐discrimination task where a spatial precue indicated the target position with 80% validity. Healthy participants (n = 29) performed this task in two runs and were required to (re‐)orient attention either only along the horizontal or the vertical meridian, while fMRI and behavioral measures were recorded. By using a general linear model for behavioral and fMRI data, dynamic causal modeling for effective connectivity, and other predictive approaches, we found strong statistical evidence for a reorientation effect for horizontal and vertical runs. However, neither neural nor behavioral measures differed between vertical and horizontal reorienting. Moreover, models from one run successfully predicted the cueing condition in the respective other run. Our results suggest that activations in the dorsal and ventral attention networks represent higher‐order cognitive processes related to spatial attentional (re‐)orientating that are independent of directional tuning and that unilateral attention deficits after brain damage are based on disrupted interactions between higher‐level attention networks and sensory areas.

Children struggle beyond preschool-age in a continuous version of the ambiguous figures task

Children until the age of five are only able to reverse an ambiguous figure when they are informed about the second interpretation. In two experiments, we examined whether children’s difficulties would extend to a continuous version of the ambiguous figures task. Children (Experiment 1: 66 3- to 5-year olds; Experiment 2: 54 4- to 9-year olds) and adult controls saw line drawings of animals gradually morph—through well-known ambiguous figures—into other animals. Results show a relatively late developing ability to recognize the target animal, with difficulties extending beyond preschool-age. This delay can neither be explained with improvements in theory of mind, inhibitory control, nor individual differences in eye movements. Even the best achieving children only started to approach adult level performance at the age of 9, suggesting a fundamentally different processing style in children and adults.

Statistical Learning Impairments as a Consequence of Stroke

Statistical learning is the implicit learning of the contingencies between sequential stimuli, typically from mere exposure. It is present from infancy onward, and plays a role in functions from language learning to selective attention. Despite these observations, there are few data on whether statistical learning capacity changes with age or after brain injury. In order to examine how brain injury affects the ability to learn and update statistical representations, we had young control and healthy elder participants, as well as participants with either left or right brain injury, perform an auditory statistical learning task. Participants listened to two languages with made-up words that were defined by the transition probability between syllables. Following passive listening, learning was assessed with a two-alternative forced choice test for the most familiar word. As in previous studies, we found that young controls have a learning capacity limitation for statistical learning; a second language is less well learned than the first, and this statistical learning capacity limit is attenuated with age. Additionally, we found that brain damaged patients, whether with left or right hemispheric damage, showed impaired statistical learning. This impairment was not explained by aphasia or cognitive deficits. As statistical learning is a critical skill for daily life, a better appreciation of the nature of this impairment will improve our understanding of the cognitive effects of brain injury and could lead to new rehabilitation strategies.

Updating impairments and the failure to explore new hypotheses following right brain damage

We have shown recently that damage to the right hemisphere impairs the ability to update mental models when evidence suggests an old model is no longer appropriate. We argue that this deficit is generic in the sense that it crosses multiple cognitive and perceptual domains. Here, we examined the nature of this updating impairment to determine more precisely the underlying mechanisms. We had right (RBD, N = 12) and left brain damaged (LBD, N = 10) patients perform versions of our picture-morphing task in which pictures gradually morph from one object (e.g., shark) to another (e.g., plane). Performance was contrasted against two groups of healthy older controls, one matched on age (HCO-age-matched, N = 9) and another matched on general level of cognitive ability (HCO-cognitively-matched, N = 9). We replicated our earlier findings showing that RBD patients took longer than LBD patients and HCOs to report seeing the second object in a sequence of morphing images. The groups did not differ when exposed to a morphing sequence a second time, or when responding to ambiguous images outside the morphing context. This indicates that RBD patients have little difficulty alternating between known representations or labeling ambiguous images. Instead, the difficulty lies in generating alternate hypotheses for ambiguous information. Lesion overlay analyses, although speculative given the sample size, are consistent with our fMRI work in healthy individuals in implicating the anterior insular cortex as critical for updating mental models.

The neural systems for perceptual updating

In a constantly changing environment we must adapt to both abrupt and gradual changes to incoming information. Previously, we demonstrated that a distributed network (including the anterior insula and anterior cingulate cortex) was active when participants updated their initial representations (e.g., it's a cat) in a gradually morphing picture task (e.g., now it's a rabbit; Stöttinger et al., 2015). To shed light on whether these activations reflect the proactive decisions to update or perceptual uncertainty, we introduced two additional conditions. By presenting picture morphs twice we controlled for uncertainty in perceptual decision making. Inducing an abrupt shift in a third condition allowed us to differentiate between a proactive decision in uncertainty-driven updating and a reactive decision in surprise-based updating. We replicated our earlier result, showing the robustness of the effect. In addition, we found activation in the anterior insula (bilaterally) and the mid frontal area/ACC in all three conditions, indicative of the importance of these areas in updating of all kinds. When participants were naïve as to the identity of the second object, we found higher activations in the mid-cingulate cortex and cuneus - areas typically associated with task difficulty, in addition to higher activations in the right TPJ most likely reflecting the shift to a new perspective. Activations associated with the proactive decision to update to a new interpretation were found in a network including the dorsal ACC known to be involved in exploration and the endogenous decision to switch to a new interpretation. These findings suggest a general network commonly engaged in all types of perceptual decision making supported by additional networks associated with perceptual uncertainty or updating provoked by either proactive or reactive decision making.

A cortical network that marks the moment when conscious representations are updated

In order to survive in a complex, noisy and constantly changing environment we need to categorize the world (e.g., Is this food edible or poisonous?) and we need to update our interpretations when things change. How does our brain update when object categories change from one to the next? We investigated the neural correlates associated with this updating process. We used event-related fMRI while people viewed a sequence of images that morphed from one object (e.g., a plane) to another (e.g., a shark). All participants were naïve as to the identity of the second object. The point at which participants 'saw' the second object was unpredictable and uncontaminated by any dramatic or salient change to the images themselves. The moment when subjective perceptual representations changed activated a circumscribed network including the anterior insula, medial and inferior frontal regions and inferior parietal cortex. In a setting where neither the timing nor nature of the visual transition was predictable, this restricted cortical network signals the time of updating a perceptual representation. The anterior insula and mid-frontal regions (including the ACC) were activated not only at the actual time when change was reported, but also immediately before, suggesting that these areas are also involved in processing alternative options after a mismatch has been detected.

Updating representations of temporal intervals

Effectively engaging with the world depends on accurate representations of the regularities that make up that world-what we call mental models. The success of any mental model depends on the ability to adapt to changes-to 'update' the model. In prior work, we have shown that damage to the right hemisphere of the brain impairs the ability to update mental models across a range of tasks. Given the disparate nature of the tasks we have employed in this prior work (i.e. statistical learning, language acquisition, position priming, perceptual ambiguity, strategic game play), we propose that a cognitive module important for updating mental representations should be generic, in the sense that it is invoked across multiple cognitive and perceptual domains. To date, the majority of our tasks have been visual in nature. Given the ubiquity and import of temporal information in sensory experience, we examined the ability to build and update mental models of time. We had healthy individuals complete a temporal prediction task in which intervals were initially drawn from one temporal range before an unannounced switch to a different range of intervals. Separate groups had the second range of intervals switch to one that contained either longer or shorter intervals than the first range. Both groups showed significant positive correlations between perceptual and prediction accuracy. While each group updated mental models of temporal intervals, those exposed to shorter intervals did so more efficiently. Our results support the notion of generic capacity to update regularities in the environment-in this instance based on temporal information. The task developed here is well suited to investigations in neurological patients and in neuroimaging settings.

Examining the influence of working memory on updating mental models

The ability to accurately build and update mental representations of our environment depends on our ability to integrate information over a variety of time scales and detect changes in the regularity of events. As such, the cognitive mechanisms that support model building and updating are likely to interact with those involved in working memory (WM). To examine this, we performed three experiments that manipulated WM demands concurrently with the need to attend to regularities in other stimulus properties (i.e., location and shape). That is, participants completed a prediction task while simultaneously performing an n-back WM task with either no load or a moderate load. The distribution of target locations (Experiment 1) or shapes (Experiments 2 and 3) included some level of probabilistic regularity, which, unbeknown to participants, changed abruptly within each block. Moderate WM load hampered the ability to benefit from target regularities and to adapt to changes in those regularities (i.e., the prediction task). This was most pronounced when both prediction and WM requirements shared the same target feature. Our results show that representational updating depends on free WM resources in a domain-specific fashion.