Perception of multi-dimensional regularities is driven by salience.

A challenge for the visual system is to detect regularities from multiple dimensions of the environment. Here we examine how regularities in multiple feature dimensions are distinguished from randomness. Participants viewed a matrix containing a structured half and a random half, and judged whether the boundary between the two halves was horizontal or vertical. In Experiments 1 and 2, the cells in the matrix varied independently in the color dimension (red or blue), the shape dimension (circle or square), or both. We found that boundary discrimination accuracy was higher when regularities were present in the color dimension than in the shape dimension, but the accuracy was the same when regularities were present in the color dimension alone or in both dimensions. By adding a third surface dimension (hollow or filled) in Experiments 3 and 4, we found that discrimination accuracy was higher when regularities were present in the surface dimension than in the color dimension, but was the same when regularities were present in the surface dimension alone or in all three dimensions. Moreover, when there were two conflicting boundaries, participants chose the boundary defined by the surface dimension, followed by the color dimension as more visible than the shape dimension (Experiments 5 and 6). Finally, participants were faster at detecting differences in the surface dimension, followed by the color and the shape dimensions (Experiments 7 and 8). These results suggest that perception of regularities in multiple feature dimensions is driven by the presence of regularities in the most salient feature dimension.

The consistency of the subjective concept of randomness.

A pervasive bias in the subjective concept of randomness is that people often expect random sequences to exhibit more alternations than produced by genuine random processes. What is less known is the stability of this bias. Here, we examine two important aspects of the over-alternation bias: first, whether this bias is present in stimuli that vary across feature dimensions, sensory modalities, presentation modes and probing methods, and, second, how consistent the bias is across these stimulus variations. In Experiment 1, participants adjusted sequences until they looked maximally random. The sequences were presented as temporal streams of colors, shapes, auditory tones or tiled as spatial matrices. In Experiment 2, participants produced random matrices by adjusting the color of each cell. We replicated the findings using a within-subjects design in Experiment 3. We found that participants judged and produced over-alternating stimuli as the most random. Importantly, this bias was consistent across presentation modes (temporal vs spatial), feature dimensions (color vs shape), sensory modalities (visual vs auditory), speed (fast vs slow), stimulus size (small vs large matrices) and probing methods (adjusting the generating process vs individual bits). Overall, the results suggest that the subjective concept of randomness is highly stable across stimulus variations.

Alternation blindness in the representation of binary sequences.

Binary information is prevalent in the environment and contains 2 distinct outcomes. Binary sequences consist of a mixture of alternation and repetition. Understanding how people perceive such sequences would contribute to a general theory of information processing. In this study, we examined how people process alternation and repetition in binary sequences. Across 4 paradigms involving estimation, working memory, change detection, and visual search, we found that the number of alternations is underestimated compared with repetitions (Experiment 1). Moreover, recall for binary sequences deteriorates as the sequence alternates more (Experiment 2). Changes in bits are also harder to detect as the sequence alternates more (Experiment 3). Finally, visual targets superimposed on bits of a binary sequence take longer to process as alternation increases (Experiment 4). Overall, our results indicate that compared with repetition, alternation in a binary sequence is less salient in the sense of requiring more attention for successful encoding. The current study thus reveals the cognitive constraints in the representation of alternation and provides a new explanation for the overalternation bias in randomness perception. (PsycINFO Database Record

Perception and identification of random events.

The cognition of randomness consists of perceptual and conceptual components. One might be able to discriminate random from nonrandom stimuli, yet be unable to identify which is which. In a series of experiments, we compare the ability to distinguish random from nonrandom stimuli to the accuracy with which given stimuli are identified as "random." In a further experiment, we also evaluate the encoding hypothesis according to which the tendency of a stimulus to be labeled random varies with the cognitive difficulty of encoding it (Falk & Konold, 1997). In our experiments, the ability to distinguish random from nonrandom stimuli is superior to the ability to correctly label them. Moreover, for at least 1 class of stimuli, difficulty of encoding fails to predict the probability of being labeled random, providing evidence against the encoding hypothesis.

A longitudinal diffusion tensor imaging study assessing white matter fiber tracts after sports-related concussion.

The extent of structural injury in sports-related concussion (SRC) is central to the course of recovery, long-term effects, and the decision to return to play. In the present longitudinal study, we used diffusion tensor imaging (DTI) to assess white matter (WM) fiber tract integrity within 2 days, 2 weeks, and 2 months of concussive injury. Participants were right-handed male varsity contact-sport athletes (20.2±1.0 years of age) with a medically diagnosed SRC (no loss of consciousness). They were compared to right-handed male varsity non-contact-sport athletes serving as controls (19.9±1.7 years). We found significantly increased radial diffusivity (RD) in concussed athletes (n=12; paired t-test, tract-based spatial statistics; p<0.025) at 2 days, when compared to the 2-week postinjury time point. The increase was found in a cluster of right hemisphere voxels, spanning the posterior limb of the internal capsule (IC), the retrolenticular part of the IC, the inferior longitudinal fasciculus, the inferior fronto-occipital fasciculus (sagittal stratum), and the anterior thalamic radiation. Post-hoc, univariate, between-group (controls vs. concussed), mixed-effects analysis of the cluster showed significantly higher RD at 2 days (p=0.002), as compared to the controls, with a trend in the same direction at 2 months (p=0.11). Results for fractional anisotropy (FA) in the same cluster showed a similar, but inverted, pattern; FA was decreased at 2 days and at 2 months postinjury, when compared to healthy controls. At 2 weeks postinjury, no statistical differences between concussed and control athletes were found with regard to either RD or FA. These results support the hypothesis of increased RD and reduced FA within 72 h postinjury, followed by recovery that may extend beyond 2 weeks. RD appears to be a sensitive measure of concussive injury.

Implicit learning of stimulus regularities increases cognitive control.

In this study we aim to examine how the implicit learning of statistical regularities of successive stimuli affects the ability to exert cognitive control. In three experiments, sequences of flanker stimuli were segregated into pairs, with the second stimulus contingent on the first. Response times were reliably faster for the second stimulus if its congruence tended to match the congruence of the preceding stimulus, even though most participants were not explicitly aware of the statistical regularities (Experiment 1). In contrast, performance was not enhanced if the congruence of the second stimuli tended to mismatch the congruence of the first stimulus (Experiment 2). The lack of improvement appears to result from a failure of learning mismatch contingencies (Experiment 3). The results suggest that implicit learning of inter-stimulus relationships can facilitate cognitive control.

Automated prediction of preferences using facial expressions.

We introduce a computer vision problem from social cognition, namely, the automated detection of attitudes from a person's spontaneous facial expressions. To illustrate the challenges, we introduce two simple algorithms designed to predict observers' preferences between images (e.g., of celebrities) based on covert videos of the observers' faces. The two algorithms are almost as accurate as human judges performing the same task but nonetheless far from perfect. Our approach is to locate facial landmarks, then predict preference on the basis of their temporal dynamics. The database contains 768 videos involving four different kinds of preferences. We make it publically available.

Category-based induction from similarity of neural activation.

The idea that similarity might be an engine of inductive inference dates back at least as far as David Hume. However, Hume's thesis is difficult to test without begging the question, since judgments of similarity may be infected by inferential processes. We present a one-parameter model of category-based induction that generates predictions about arbitrary statements of conditional probability over a predicate and a set of items. The prediction is based on the unconditional probabilities and similarities that characterize that predicate and those items. To test Hume's thesis, we collected brain activation from various regions of the ventral visual stream during a categorization task that did not invite comparison of categories. We then calculated the similarity of those activation patterns using a simple measure of vectorwise similarity and supplied those similarities to the model. The model's outputs correlated well with subjects' judgments of conditional probability. Our results represent a promising first step toward confirming Hume's thesis; similarity, assessed without reference to induction, may well drive inductive inference.

Persistent differences in patterns of brain activation after sports-related concussion: a longitudinal functional magnetic resonance imaging study.

Avoiding recurrent injury in sports-related concussion (SRC) requires understanding the neural mechanisms involved during the time of recovery after injury. The decision for return-to-play is one of the most difficult responsibilities facing the physician, and so far this decision has been based primarily on neurological examination, symptom checklists, and neuropsychological (NP) testing. Functional magnetic resonance imaging (fMRI) may be an additional, more objective tool to assess the severity and recovery of function after concussion. The purpose of this study was to define neural correlates of SRC during the 2 months after injury in varsity contact sport athletes who suffered a SRC. All athletes were scanned as they performed an n-back task, for n=1, 2, 3. Subjects were scanned within 72 hours (session one), at 2 weeks (session two), and 2 months (session three) post-injury. Compared with age and sex matched normal controls, concussed subjects demonstrated persistent, significantly increased activation for the 2 minus 1 n-back contrast in bilateral dorsolateral prefrontal cortex (DLPFC) in all three sessions and in the inferior parietal lobe in session one and two (α≤0.01 corrected). Measures of task performance revealed no significant differences between concussed versus control groups at any of the three time points with respect to any of the three n-back tasks. These findings suggest that functional brain activation differences persist at 2 months after injury in concussed athletes, despite the fact that their performance on a standard working memory task is comparable to normal controls and normalization of clinical and NP test results. These results might indicate a delay between neural and behaviorally assessed recovery after SRC.

Thought beyond language: neural dissociation of algebra and natural language.

A central question in cognitive science is whether natural language provides combinatorial operations that are essential to diverse domains of thought. In the study reported here, we addressed this issue by examining the role of linguistic mechanisms in forging the hierarchical structures of algebra. In a 3-T functional MRI experiment, we showed that processing of the syntax-like operations of algebra does not rely on the neural mechanisms of natural language. Our findings indicate that processing the syntax of language elicits the known substrate of linguistic competence, whereas algebraic operations recruit bilateral parietal brain regions previously implicated in the representation of magnitude. This double dissociation argues against the view that language provides the structure of thought across all cognitive domains.

Updating: learning versus supposing.

Bayesian orthodoxy posits a tight relationship between conditional probability and updating. Namely, the probability of an event A after learning B should equal the conditional probability of A given B prior to learning B. We examine whether ordinary judgment conforms to the orthodox view. In three experiments we found substantial differences between the conditional probability of an event A supposing an event B compared to the probability of A after having learned B. Specifically, supposing B appears to have less impact on the credibility of A than learning that B is true.

Logic, language and the brain.

What is the role of language in human cognition? Within the domain of deductive reasoning, the issue has been the focus of numerous investigations without the emergence of a consensus view. Here we consider some of the reasons why neuroimaging studies of deductive reasoning have generated mixed results. We then review recent evidence suggesting that the role of language in deductive reasoning is confined to an initial stage in which verbally presented information is encoded as non-verbal representations. These representations are then manipulated by mental operations that are not based on the neural mechanisms of natural language. This article is part of a Special Issue entitled "The Cognitive Neuroscience".

Evidence for conceptual combination in the left anterior temporal lobe.

Conceptual combination allows for the construction of an infinite number of complex ideas from a finite base. The anterior temporal lobes appear to be important for the process of conceptual combination. In a previous study (Baron et al., 2010) we showed that the neural representation of complex concepts (e.g., young man) in the left anterior temporal lobe is additive. Specifically, in that region, the representation of a complex concept can be predicted by the superimposition of the voxel-wise neural representations of its constituent concepts (e.g., young+man). However, this finding could be the result of phonological similarity or the simple co-activation of constituent concepts. Here we use concepts that are only related semantically: boy, girl, woman, man, female, male, child, and adult. The neural representation for each concept was evoked through a visual categorization task. Subsequent brain maps were then analyzed using a searchlight analysis meant to show areas of the cortex where multiplicative (as well as additive) conceptual combination occurred (e.g., areas in which activations for boy correlated with the product of the activations for male and child). Across all participants, the left anterior temporal lobe showed such an effect.

Second-order probability affects hypothesis confirmation.

Bayesian confirmation measures give numerical expression to the impact of evidence E on a hypothesis H. All measures proposed to date are formal-that is, functions of the probabilities Pr[see equation in text], Pr[see equation in text], Pr[see equation in text], Pr[see equation in text], and nothing more. Experiments reported in Tentori, Crupi, and Osherson (2007) suggest that human confirmation judgment is not formal, but this earlier work leaves open the possibility that formality holds relative to a given semantic domain. The present study discredits even this weaker version of formality by demonstrating the role in confirmation judgments of a probability distribution defined over the possible values of Pr[see equation in text], Pr[see equation in text], Pr[see equation in text], and Pr[see equation in text]-that is, a second-order probability. Specifically, when for each of the latter quantities a pointwise value is fixed with a maximal second-order probability, evidence impact is rated in accordance with formal and normatively credible confirmation measures; otherwise evidence impact is systematically judged as more moderate.

An early stage of conceptual combination: Superimposition of constituent concepts in left anterolateral temporal lobe.

Conceptual combination is an essential cognitive process, yet little is known about its neural correlates. In the present study, a categorization task was used to evoke patterns of neural activation for complex concepts (e.g., young man) as well as their constituents (e.g., young, man). A functional region of interest (fROI) within left anterolateral temporal lobe was identified as a possible site of conceptual combination. In this region, the superimposition of activity for constituent concepts reliably predicted the activation pattern for the complex concept built from those constituents.

On the provenance of judgments of conditional probability.

In standard treatments of probability, Pr(A|B) is defined as the ratio of Pr(A intersectionB) to Pr(B), provided that Pr(B)>0. This account of conditional probability suggests a psychological question, namely, whether estimates of Pr(A|B) arise in the mind via implicit calculation of Pr(A intersectionB)/Pr(B). We tested this hypothesis (Experiment 1) by presenting brief visual scenes composed of forms, and collecting estimates of relevant probabilities. Direct estimates of conditional probability were not well predicted by Pr(A intersectionB)/Pr(B). Direct estimates were also closer to the objective probabilities defined by the stimuli, compared to estimates computed from the foregoing ratio. The hypothesis that Pr(A|B) arises from the ratio Pr(A intersectionB)/[Pr(A intersectionB)+Pr(A intersectionB)] fared better (Experiment 2). In a third experiment, the same hypotheses were evaluated in the context of subjective estimates of the chance of future events.

The boundaries of language and thought in deductive inference.

Is human thought fully embedded in language, or do some forms of thought operate independently? To directly address this issue, we focus on inference-making, a central feature of human cognition. In a 3T fMRI study we compare logical inferences relying on sentential connectives (e.g., not, or, if ... then) to linguistic inferences based on syntactic transformation of sentences involving ditransitive verbs (e.g., give, say, take). When contrasted with matched grammaticality judgments, logic inference alone recruited "core" regions of deduction [Brodmann area (BA) 10p and 8m], whereas linguistic inference alone recruited perisylvian regions of linguistic competence, among others (BA 21, 22, 37, 39, 44, and 45 and caudate). In addition, the two inferences commonly recruited a set of general "support" areas in frontoparietal cortex (BA 6, 7, 8, 40, and 47). The results indicate that logical inference is not embedded in natural language and confirm the relative modularity of linguistic processes.

Predicting judged similarity of natural categories from their neural representations.

We report a combined behavioral and functional magnetic resonance imaging (fMRI) study of conceptual similarity among members of a natural category (mammals). The study examined the relationship between computed pairwise similarity of neural responses to viewed mammals (e.g. bear, camel, dolphin) and subjective pairwise similarity ratings of the same set of mammals, obtained from subjects after the scanning session. In each functional region of interest (fROI), measures of neural similarity were compared to behavioral ratings. fROIs were identified as clusters of voxels that discriminated intact versus scrambled images of mammals (no information about similarity was used to define fROIs). Neural similarity was well correlated with behavioral ratings in fROIs covering the lateral occipital complex in both hemispheres (with overlap of the fusiform and inferior temporal gyri on the right side). The latter fROIs showed greater hemodynamic response to intact versus scrambled images of mammals whereas the fROIs that failed to predict similarity showed the reverse pattern. The findings provide novel evidence that information about the fine structure of natural categories is coarsely coded in regions of the ventral visual pathway. Implications for the theory of inductive inference are discussed.

Determinants of confirmation.

Epistemologists often suppose that the extent to which evidence e confirms hypothesis H depends on probabilities involving e and H, and nothing more. We show experimentally that human reasoners sometimes violate this assumption.

Induction as conditional probability judgment.

Existing research on category-based induction has primarily focused on reasoning about blank properties, or predicates that are designed to elicit little prior knowledge. Here, we address reasoning about nonblank properties. We introduce a model of conditional probability that assumes that the conclusion prior probability is revised to the extent warranted by the evidence in the premise. The degree of revision is a function of the relevance of the premise category to the conclusion and the informativeness of the premise statement. An algebraic formulation with no free parameters accurately predicted conditional probabilities for single- and two-premise conditionals (Experiments 1 and 3), as well as problems involving negative evidence (Experiment 2).