Catherine Hanson

Six problems for causal inference from fMRI

Neuroimaging (e.g. fMRI) data are increasingly used to attempt to identify not only brain regions of interest (ROIs) that are especially active during perception, cognition, and action, but also the qualitative causal relations among activity in these regions (known as effective connectivity; Friston, 1994). Previous investigations and anatomical and physiological knowledge may somewhat constrain the possible hypotheses, but there often remains a vast space of possible causal structures. To find actual effective connectivity relations, search methods must accommodate indirect measurements of nonlinear time series dependencies, feedback, multiple subjects possibly varying in identified regions of interest, and unknown possible location-dependent variations in BOLD response delays. We describe combinations of procedures that under these conditions find feed-forward sub-structure characteristic of a group of subjects. The method is illustrated with an empirical data set and confirmed with simulations of time series of non-linear, randomly generated, effective connectivities, with feedback, subject to random differences of BOLD delays, with regions of interest missing at random for some subjects, measured with noise approximating the signal to noise ratio of the empirical data.

Atypical effective connectivity of social brain networks in individuals with autism.

Failing to engage in joint attention is a strong marker of impaired social cognition associated with autism spectrum disorder (ASD). The goal of this study was to localize the source of impaired joint attention in individuals with ASD by examining both behavioral and fMRI data collected during various tasks involving eye gaze, directional cuing, and face processing. The tasks were designed to engage three brain networks associated with social cognition [face processing, theory of mind (TOM), and action understanding]. The behavioral results indicate that even high-functioning individuals with ASD perform less accurately and more slowly than neurotypical (NT) controls when processing eyes, but not when processing a directional cue (an arrow) that did not involve eyes. Behavioral differences between the NT and ASD groups were consistent with differences in the effective connectivity of FACE, TOM, and ACTION networks. An independent multiple-sample greedy equivalence search was used to examine these social brain networks and found that whereas NTs produced stable patterns of response across tasks designed to engage a given brain network, ASD participants did not. Moreover, ASD participants recruited all three networks in a manner highly dissimilar to that of NTs. These results extend a growing literature that describes disruptions in general brain connectivity in individuals with autism by targeting specific networks hypothesized to underlie the social cognitive impairments observed in these individuals.

Development of schemata during event parsing: Neisser's perceptual cycle as a recurrent connectionist network

Neural net simulations of human event parsing are described. A recurrent net was used to simulate data collected from human subjects watching short videotaped event sequences. In one simulation, the net was trained on one-half of a taped sequence with the other half of the sequence being used to test transfer performance. In another simulation, the net was trained on one complete event sequence and transfer to a different event sequence was tested. Neural net simulations provide a unique means of observing the interrelation of top-down and bottom-up processing in a basic cognitive task. Examination of computational patterns of the net and cluster analysis of the hidden units revealed two factors that may be central to event perception: (1) similarity between a current input and an activated schema and (2) expected duration of a given event. Although the importance of similarity between input and activated schemata during event perception has been acknowledged previously (e.g., Neisser, 1976; Schank, 1982), the present study provides specific instantiation of how similarity judgments can be made using both top-down and bottom-up processing. Moreover, unlike other work on event perception, this approach provides a potential mechanism for how schemata develop.

Solving the brain synchrony eigenvalue problem: conservation of temporal dynamics (fMRI) over subjects doing the same task

Brain measures often show highly structured temporal dynamics that synchronize when observers are doing the same task. The standard method for analysis of brain imaging signals (e.g. fMRI) uses the GLM for each voxel indexed against a specified experimental design but does not explicitly involve temporal dynamics. Consequently, the design variables that determine the functional brain areas are those correlated with the design variation rather than the common or conserved brain areas across subjects with the same temporal dynamics given the same stimulus conditions. This raises an important theoretical question: Are temporal dynamics conserved across individuals experiencing the same stimulus task? This general question can be framed in a dynamical systems context and further be posed as an eigenvalue problem about the conservation of synchrony across all brains simultaneously. We show that solving the problem results in a non-arbitrary measure of temporal dynamics across brains that scales over any number of subjects, stabilizes with increasing sample size, and varies systematically across tasks and stimulus conditions.

fMRI BOLD response in high-risk college students (Part 1): during exposure to alcohol, marijuana, polydrug and emotional picture cues.

AIM This functional magnetic resonance imaging (fMRI) study examined reactivity to alcohol, polydrug, marijuana and emotional picture cues in students who were referred to a college alcohol and drug assistance program. METHODS The fMRI data of 10 participants (5 females; 5 males) were collected while they viewed standardized emotional and appetitive cues. RESULTS Positive and negative emotional cues produced greater activity than neutral cues in the expected brain areas. Compared with neutral cues, alcohol cues produced greater brain activation in the right insula, left anterior cingulate, left caudate and left prefrontal cortex (Z = 2.01, 1.86, 1.82, 1.81, respectively; P < 0.05). Drug cues produced significantly greater left prefrontal activity compared with neutral cues, with polydrug cues activating the right insula and marijuana cues activating left anterior cingulate. CONCLUSIONS Students at-risk for alcohol abuse showed neural reactivity to alcohol cues in four brain regions, which is consistent with their greater use of alcohol. Insula activation to appetitive cues may be an early marker of risk for progression to alcohol/drug abuse.

Bottom-up and top-down brain functional connectivity underlying comprehension of everyday visual action

How can the components of visual comprehension be characterized as brain activity? Making sense of a dynamic visual world involves perceiving streams of activity as discrete units such as eating breakfast or walking the dog. In order to parse activity into distinct events, the brain relies on both the perceptual (bottom-up) data available in the stimulus as well as on expectations about the course of the activity based on previous experience with, or knowledge about, similar types of activity (top-down data). Using fMRI, we examined the contribution of bottom-up and top-down processing to the comprehension of action streams by contrasting familiar action sequences with those having exactly the same perceptual detection and motor responses (yoked control), but no visual action familiarity. New methods incorporating structural equation modeling of the data yielded distinct patterns of interactivity among brain areas as a function of the degree to which bottom-up and top-down data were available.

Modeling Causal Relationship Between Brain Regions Within the Drug-Cue Processing Network in Chronic Cocaine Smokers.

The cues associated with drugs of abuse have an essential role in perpetuating problematic use, yet effective connectivity or the causal interaction between brain regions mediating the processing of drug cues has not been defined. The aim of this fMRI study was to model the causal interaction between brain regions within the drug-cue processing network in chronic cocaine smokers and matched control participants during a cocaine-cue exposure task. Specifically, cocaine-smoking (15M; 5F) and healthy control (13M; 4F) participants viewed cocaine and neutral cues while in the scanner (a Siemens 3 T magnet). We examined whole brain activation, including activation related to drug-cue processing. Time series data extracted from ROIs determined through our General Linear Model (GLM) analysis and prior publications were used as input to IMaGES, a computationally powerful Bayesian search algorithm. During cocaine-cue exposure, cocaine users showed a particular feed-forward effective connectivity pattern between the ROIs of the drug-cue processing network (amygdalahippocampusdorsal striatuminsulamedial frontal cortex, dorsolateral prefrontal cortex, anterior cingulate cortex) that was not present when the controls viewed the cocaine cues. Cocaine craving ratings positively correlated with the strength of the causal influence of the insula on the dorsolateral prefrontal cortex in cocaine users. This study is the first demonstration of a causal interaction between ROIs within the drug-cue processing network in cocaine users. This study provides insight into the mechanism underlying continued substance use and has implications for monitoring treatment response.

Implicit memory for object locations depends on reactivation of encoding-related brain regions†

This study explored the correspondence between implicit memory and the reactivation of encoding‐related brain regions. By using a classification method, we examined whether reactivation reflects only the similarities between study and test or voxels at the reactivated regions are diagnostic of facilitation in the implicit memory task. A simple detection task served as incidental encoding of object–location pairings. A subsequent visual search task served as the indirect (implicit) test of memory. Subjects did not know that their memory would be tested. Half of the subjects were unaware that some stimuli in the search task are the same as those that had appeared during the detection task. Another group of subjects was made aware of this relationship at the onset of the visual search task. Memory performance was superior for the study‐test aware, compared to study‐test unaware, subjects. Brain reactivation was calculated using a conjunction analysis implemented through overlaying the neural activity at encoding and testing. The conjunction analysis revealed that implicit memory in both groups of subjects was associated with reactivation of parietal and occipital brain regions. We were able to classify study‐test aware and study‐test unaware subjects based on the per‐voxel reactivation values representing the neural dynamics between encoding and test. The classification results indicate that neural dynamics between encoding and test accounts for the differences in implicit memory. Overall, our study demonstrates that implicit memory performance requires and depends upon reactivation of encoding‐related brain regions. Hum Brain Mapp, 2010.

Seeing is worse than believing: Reading people's minds better than computer-vision methods recognize actions

We had human subjects perform a one-out-of-six class action recognition task from video stimuli while undergoing functional magnetic resonance imaging (fMRI). Support-vector machines (SVMs) were trained on the recovered brain scans to classify actions observed during imaging, yielding average classification accuracy of 69.73% when tested on scans from the same subject and of 34.80% when tested on scans from different subjects. An apples-to-apples comparison was performed with all publicly available software that implements state-of-the-art action recognition on the same video corpus with the same cross-validation regimen and same partitioning into training and test sets, yielding classification accuracies between 31.25% and 52.34%. This indicates that one can read people’s minds better than state-of-the-art computer-vision methods can perform action recognition.

Brain network response underlying decisions about abstract reinforcers

Decision making studies typically use tasks that involve concrete action-outcome contingencies, in which subjects do something and get something. No studies have addressed decision making involving abstract reinforcers, where there are no action-outcome contingencies and choices are entirely hypothetical. The present study examines these kinds of choices, as well as whether the same biases that exist for concrete reinforcer decisions, specifically framing effects, also apply during abstract reinforcer decisions. We use both General Linear Model as well as Bayes network connectivity analysis using the Independent Multi-sample Greedy Equivalence Search (IMaGES) algorithm to examine network response underlying choices for abstract reinforcers under positive and negative framing. We find for the first time that abstract reinforcer decisions activate the same network of brain regions as concrete reinforcer decisions, including the striatum, insula, anterior cingulate, and VMPFC, results that are further supported via comparison to a meta-analysis of decision making studies. Positive and negative framing activated different parts of this network, with stronger activation in VMPFC during negative framing and in DLPFC during positive, suggesting different decision making pathways depending on frame. These results were further clarified using connectivity analysis, which revealed stronger connections between anterior cingulate, insula, and accumbens during negative framing compared to positive. Taken together, these results suggest that not only do abstract reinforcer decisions rely on the same brain substrates as concrete reinforcers, but that the response underlying framing effects on abstract reinforcers also resemble those for concrete reinforcers, specifically increased limbic system connectivity during negative frames.