A multimodal fMRI dataset unifying naturalistic processes with a rich array of experimental tasks.

Cognitive neuroscience has advanced significantly due to the availability of openly shared datasets. Large sample sizes, large amounts of data per person, and diversity in tasks and data types are all desirable, but are difficult to achieve in a single dataset. Here, we present an open dataset with N = 101 participants and 6 hours of scanning per participant, with 6 multifaceted cognitive tasks including 2 hours of naturalistic movie viewing. This datasets' combination of ample sample size, extensive data per participant, more than 600 hours worth of data, and a wide range of experimental conditions - including cognitive, affective, social, and somatic/interoceptive tasks - positions it uniquely for probing important questions in cognitive neuroscience.

The push-pull of serial dependence effects: Attraction to the prior response and repulsion from the prior stimulus.

In the "serial dependence" effect, responses to visual stimuli appear biased toward the last trial's stimulus. However, several kinds of serial dependence exist, with some reflecting prior stimuli and others reflecting prior responses. One-factor analyses consider the prior stimulus alone or the prior response alone and can consider both variables only via separate analyses. We demonstrate that one-factor analyses are potentially misleading and can reach conclusions that are opposite from the truth if both dependencies exist. To address this limitation, we developed two-factor analyses (model comparison with hierarchical Bayesian modeling and an empirical "quadrant analysis"), which consider trial-by-trial combinations of prior response and prior stimulus. Two-factor analyses can tease apart the two dependencies if applied to a sufficiently large dataset. We applied these analyses to a new study and to four previously published studies. When applying a model that included the possibility of both dependencies, there was no evidence of attraction to the prior stimulus in any dataset, but there was evidence of attraction to the prior response in all datasets. Two of the datasets contained sufficient constraint to determine that both dependencies were needed to explain the results. For these datasets, the dependency on the prior stimulus was repulsive rather than attractive. Our results are consistent with the claim that both dependencies exist in most serial dependence studies (the two-dependence model was not ruled out for any dataset) and, furthermore, that the two dependencies work against each other.

A modeling framework for determining modulation of neural-level tuning from non-invasive human fMRI data.

Many neuroscience theories assume that tuning modulation of individual neurons underlies changes in human cognition. However, non-invasive fMRI lacks sufficient resolution to visualize this modulation. To address this limitation, we developed an analysis framework called Inferring Neural Tuning Modulation (INTM) for "peering inside" voxels. Precise specification of neural tuning from the BOLD signal is not possible. Instead, INTM compares theoretical alternatives for the form of neural tuning modulation that might underlie changes in BOLD across experimental conditions. The most likely form is identified via formal model comparison, with assumed parametric Normal tuning functions, followed by a non-parametric check of conclusions. We validated the framework by successfully identifying a well-established form of modulation: visual contrast-induced multiplicative gain for orientation tuned neurons. INTM can be applied to any experimental paradigm testing several points along a continuous feature dimension (e.g., direction of motion, isoluminant hue) across two conditions (e.g., with/without attention, before/after learning).

A Roadmap for Understanding Memory: Decomposing Cognitive Processes into Operations and Representations.

Thanks to patients Phineas Gage and Henry Molaison, we have long known that behavioral control depends on the frontal lobes, whereas declarative memory depends on the medial temporal lobes (MTL). For decades, cognitive functions-behavioral control, declarative memory-have served as labels for characterizing the division of labor in cortex. This approach has made enormous contributions to understanding how the brain enables the mind, providing a systems-level explanation of brain function that constrains lower-level investigations of neural mechanism. Today, the approach has evolved such that functional labels are often applied to brain networks rather than focal brain regions. Furthermore, the labels have diversified to include both broadly-defined cognitive functions (declarative memory, visual perception) and more circumscribed mental processes (recollection, familiarity, priming). We ask whether a process-a high-level mental phenomenon corresponding to an introspectively-identifiable cognitive event-is the most productive label for dissecting memory. For example, recollection conflates a neurocomputational operation (pattern completion-based retrieval) with a class of representational content (associative, high-dimensional memories). Because a full theory of memory must identify operations and representations separately, and specify how they interact, we argue that processes like recollection constitute inadequate labels for characterizing neural mechanisms. Instead, we advocate considering the component operations and representations of processes like recollection in isolation. For the organization of memory, the evidence suggests that pattern completion is recapitulated widely across the ventral visual stream and MTL, but the division of labor between sites within this pathway can be explained by representational content.

Connecting the dots without top-down knowledge: Evidence for rapidly-learned low-level associations that are independent of object identity.

Knowing the identity of an object can powerfully alter perception. Visual demonstrations of this-such as Gregory's (1970) hidden Dalmatian-affirm the existence of both top-down and bottom-up processing. We consider a third processing pathway: lateral connections between the parts of an object. Lateral associations are assumed by theories of object processing and hierarchical theories of memory, but little evidence attests to them. If they exist, their effects should be observable even in the absence of object identity knowledge. We employed Continuous Flash Suppression (CFS) while participants studied object images, such that visual details were learned without explicit object identification. At test, lateral associations were probed using a part-to-part matching task. We also tested whether part-whole links were facilitated by prior study using a part-naming task, and included another study condition (Word), in which participants saw only an object's written name. The key question was whether CFS study (which provided visual information without identity) would better support part-to-part matching (via lateral associations) whereas Word study (which provided identity without the correct visual form) would better support part-naming (via top-down processing). The predicted dissociation was found and confirmed by state-trace analyses. Thus, lateral part-to-part associations were learned and retrieved independently of object identity representations. This establishes novel links between perception and memory, demonstrating that (a) lateral associations at lower levels of the object identification hierarchy exist and contribute to object processing and (b) these associations are learned via rapid, episodic-like mechanisms previously observed for the high-level, arbitrary relations comprising episodic memories. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A hierarchical Bayesian state trace analysis for assessing monotonicity while factoring out subject, item, and trial level dependencies.

State trace analyses assess the latent dimensionality of a cognitive process by asking whether the means of two dependent variables conform to a monotonic function across a set of conditions. Using an assumption of independence between the measures, recently proposed statistical tests address bivariate measurement error, allowing both frequentist and Bayesian analyses of monotonicity (e.g., Davis-Stober, Morey, Gretton, & Heathcote, 2016; Kalish, Dunn, Burdakov, & Sysoev, 2016). However, inference can be biased by unacknowledged dependencies between measures, particularly when the data are insufficient to overwhelm an incorrect prior assumption of independence. To address this limitation, we developed a hierarchical Bayesian model that explicitly models the separate roles of subject, item, and trial-level dependencies between two measures. Assessment of monotonicity is then performed by fitting separate models that do or do not allow a non-monotonic relation between the condition effects (i.e., same vs. different rank orders). The Widely Applicable Information Criterion (WAIC) and Pseudo Bayesian Model Averaging - cross validation measures of model fit - are used for model comparison, providing an inferential conclusion regarding the dimensionality of the latent psychological space. We validated this new state trace analysis technique using model recovery simulation studies, which assumed different ground truths regarding monotonicity and the direction/magnitude of the subject- and trial-level dependence. We also provide an example application of this new technique to a visual object learning study that compared performance on a visual retrieval task (forced choice part recognition) versus a verbal retrieval task (cued recall).

Hippocampal Engagement during Recall Depends on Memory Content.

The hippocampus is considered pivotal to recall, allowing retrieval of information not available in the immediate environment. In contrast, neocortex is thought to signal familiarity, contributing to recall only when called upon by the hippocampus. However, this view is not compatible with representational accounts of memory, which reject the mapping of cognitive processes onto brain regions. According to representational accounts, the hippocampus is not engaged by recall per se, rather it is engaged whenever hippocampal representations are required. To test whether hippocampus is engaged by recall when hippocampal representations are not required, we used functional imaging and a non-associative recall task, with images (objects, scenes) studied in isolation, and image patches as cues. As predicted by a representational account, hippocampal activation was modulated by the content of the recalled memory, increasing during recall of scenes-which are known to be processed by hippocampus-but not during recall of objects. Object recall instead engaged neocortical regions known to be involved in object-processing. Further supporting the representational account, effective connectivity analyses revealed that changes in functional activation during recall were driven by increased information flow from neocortical sites, rather than by the spreading of recall-related activation from hippocampus back to neocortex.

A Computational Model of Perceptual and Mnemonic Deficits in Medial Temporal Lobe Amnesia.

Damage to the medial temporal lobe (MTL) has long been known to impair declarative memory, and recent evidence suggests that it also impairs visual perception. A theory termed the representational-hierarchical account explains such impairments by assuming that MTL stores conjunctive representations of items and events, and that individuals with MTL damage must rely upon representations of simple visual features in posterior visual cortex, which are inadequate to support memory and perception under certain circumstances. One recent study of visual discrimination behavior revealed a surprising antiperceptual learning effect in MTL-damaged individuals: With exposure to a set of visual stimuli, discrimination performance worsened rather than improved [Barense, M. D., Groen, I. I. A., Lee, A. C. H., Yeung, L. K., Brady, S. M., Gregori, M., et al. Intact memory for irrelevant information impairs perception in amnesia. Neuron, 75, 157-167, 2012]. We extend the representational-hierarchical account to explain this paradox by assuming that difficult visual discriminations are performed by comparing the relative "representational tunedness"-or familiarity-of the to-be-discriminated items. Exposure to a set of highly similar stimuli entails repeated presentation of simple visual features, eventually rendering all feature representations maximally and, thus, equally familiar; hence, they are inutile for solving the task. Discrimination performance in patients with MTL lesions is therefore impaired by stimulus exposure. Because the unique conjunctions represented in MTL do not occur repeatedly, healthy individuals are shielded from this perceptual interference. We simulate this mechanism with a neural network previously used to explain recognition memory, thereby providing a model that accounts for both mnemonic and perceptual deficits caused by MTL damage with a unified architecture and mechanism.