The Method of Loci revisited: Virtually augmented memory palaces [ICPS 2017 Symposium Presentation]

Symposium talk presented at ICPS 2017 in Vienna, Austria

Abstract:

Humans have long appreciated that visuospatial cues can serve as a scaffolding for the encoding of non-spatial content. The Method of Loci (MoL), which binds objects to a spatial context in one’s mental imagery, has helped enhance the mnemonic retrieval processes of memory champions since Ancient Greece. An adaptation of this method that seamlessly extends such benefits to the mass market could revolutionize how we process and convey information. At the forefront of such development is a startup company named Altar that has has begun the productization of a virtual Method of Loci, called Altar Show. This novel virtual reality presentation software is already being used in contexts ranging from business pitches, to secondary education and employee training.

Presentation: Reggente_ICPS_2017_Symposium

Prediction of response to cognitive-behavioral therapy in obsessive-compulsive disorder: a multivariate analysis of resting state functional connectivity

Jamie D Feusner, MD1; Nicco Reggente, MA2; Teena D Moody, PhD1; Francesca Morfini, MA1; Jesse Rissman, PhD1,2; Joseph O’Neill, PhD1

Affiliation:

1Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California 2Department of Psychology, UCLA, Los Angeles, California

Background: Cognitive-behavioral therapy (CBT) is an effective treatment for reducing symptoms of obsessive-compulsive disorder (OCD). Although many with OCD will benefit from CBT, the response still varies significantly between individuals. In addition, specialized CBT for OCD has limited availability, can be an expensive treatment, and by its nature is stressful and often time-consuming. This underscores the importance of developing reliable predictors of response to treatment to help with clinical decision-making. Although several studies have examined clinical and neurobiological features pre-treatment that are correlated with response to treatment, only one has examined functional connectivity as a predictor, and none have applied multivariate approaches. We used a multivariate pattern recognition approach applied to resting state functional connectivity pre-CBT in order to make predictive inferences on the individual patient level, as to their degree of response to treatment. In addition, we applied the same approaches to pre-treatment symptomatology in order to further elucidate mechanisms of functional connectivity associated with obsessions and compulsions, in a data-driven manner.

Methods: We acquired resting state functional magnetic resonance image BOLD data in 25 medicated and unmedicated adults with OCD before 4 weeks of intensive daily exposure and response prevention, a form of CBT. Core OCD symptomatology was measured using the Yale-Brown Obsessive Compulsive Scale (YBOCS). Image preprocessing included parcellation of the brain into 264 regions of interest, each belonging to one of 14 functional networks previously derived from meta-analyses of functional studies. We computed a pairwise Pearson-correlation matrix for each mean time course resulting in a 264 x 264 matrix containing the pairwise functional connectivity values (r-values) across all ROIs. Matrix cells corresponding to each functional network were identified to create feature sets. We implemented a leave-one-patient-out cross-validation to assess the predictive power of our feature sets in regards to our behavioral measures of interest: change in YBOCS scores from pre- to post-CBT. Specifically, we built a least absolute shrinkage and selection operator (LASSO) regression model on n-1 patients using their feature sets. We correlated the predicted values with the actual values in order to yield a multiple R2 as a measure of our model’s feature-dependent predictivity. Additionally, we applied the same analysis to the pre-CBT (baseline) YBOCS scores.

Results: OCD participants showed significant clinical symptom improvements pre- to post-CBT (YBOCS scores X±Y pre-CBT; Z±Q post-CBT; t26=P, p<.R). Connectivity strength in the ventral attention network predicted greater/lesser reduction of YBOCS scores pre- to post-CBT ( =.185, P=.01. Connectivity strength in the cingulo-opercular network at baseline was predictive of baseline severity of YBOCS scores ( =.35, P=.0009).

Conclusions: This represents the first study in OCD to use multivariate pattern recognition approaches to determine neurobiological markers predictive of response to treatment. Strength of resting state functional connectivity in the ventral attention network was associated with a better response to treatment. This may signify that those with better inherent ability to attend to perceptually-driven stimuli in their environment (perhaps also reflecting that they are less internally distracted by obsessive thoughts) may respond better to treatment. In addition, the phenomenology of obsessions and compulsions, specifically before treatment, is associated with connectivity in the cingulo-opercular network. Given the function of this network, those with weaker connectivity may be less able to maintain control over behaviors and thought patterns in the face of emotional arousal, and hence have higher degree of obsessions and compulsions. Results have clinical implications for identifying individual OCD patients who will maximally benefit from treatment with intensive CBT, and have implications for further understanding the pathophysiology of OCD.

View the Poster, Presented at ACNP (2016)

The Method of Loci revisited: Memory enhancement by way of virtually augmented memory palaces

Reggente, N., Essoe, J., Mehta, P.*, Ohno, A.*, Rissman, J.

Humans have long appreciated that visuospatial cues can serve as a scaffolding for the encoding of non-spatial content. The Method of Loci (MoL), which binds objects to a spatial context in one’s mental imagery, has been the favored mnemonic strategy of memory champions since Ancient Greece. In this work, we created a virtual reality implementation of the MoL to tease apart the factors that contribute to the MoL’s undeniable efficacy as a memory enhancement technique. We crafted three distinct virtual environments where subjects could view objects. Subjects that were told to place items at locations of their choosing recalled significantly more objects than subjects who only viewed the objects. We also addressed the contributions of volition and contextual richness to recall strength.

View the poster, presented at ICOM in Budapest (2016)

Neural correlates of fluid intelligence via functional and structural network connectivity measures

Connectivity across regions in the brain can be characterized as either functional (correlated fluctuations in activity as measured by resting-state fMRI data) or structural (white matter pathways as measured by diffusion MRI data). Emerging studies suggest that the connections across brain regions that make up distinct cognitive networks can partially explain individual differences in behavioral traits. Some theorize that a reliable benchmark of intelligence is the ability to identify subtle patterns across distantly related ideas. The Raven’s Progressive Matrices (RPM), a pattern completion task, is one widely used measure of general fluid intelligence. Here, we use a combination of functional and structural connectivity metrics derived from a large MRI dataset [n=127] to examine the relationship between neural connectivity and RPM scores. We used a Support Vector Regression cross-validation procedure to assess the degree to which we could predict a subject’s intelligence based on these connectivity values. We were able to account for 14% of the variance in individuals’ intelligence scores when using specific combinations of functional and structural connectivity values.

You can view our poster here:

Vuong, Reggente, Rissman Poster Presented at UCLA PURC 2016

Disentangling Disorders of Consciousness: Insights from Diffusion Tensor Imaging and Machine Learning

Abstract: Previous studies have suggested that disorders of consciousness (DOC) after severe brain injury may result from disconnections of the thalamo-cortical system. However, thalamo-cortical connectivity differences between vegetative state (VS), minimally conscious state minus (MCS-,i.e., low-level behavior such as visual pursuit), and minimally conscious state plus (MCS+, i.e., high-level behavior such as language processing) remain unclear. We employed probabilistic tractography in a sample of 25 DOC patients to assess whether structural connectivity in various thalamo-cortical circuits could differentiate between VS, MCS-, and MCS+ patients. First, we individually segmented the thalamus into seven clusters based on patterns of cortical connectivity and tested for univariate differences across groups. Second, reconstructed wholebrain thalamic tracks were used as features in a multivariate searchlight analysis to identify regions along the tracks that were most informative in distinguishing among groups. At the univariate level, we found that VS patients displayed reduced connectivity in most thalamocortical circuits of interest, including frontal, temporal, and sensorimotor connections, as compared to MCS+, but showed more pulvinar-occipital connections when compared to MCS-.Moreover, MCS- exhibited significantly less thalamo-premotor and thalamo-temporal connectivity than MCS+. At the multivariate level, we found that thalamic tracks reaching frontal, parietal, and sensorimotor regions, could discriminate, up to 100% accuracy, across each pairwise group comparison. Together, these findings highlight the role of thalamo-cortical connections in patients’ behavioral profile and level of consciousness. Diffusion tensor imaging combined with machine learning algorithms could thus potentially facilitate diagnostic distinctions in DOC and shed light on the neural correlates of consciousness.

Disentangling Disorders of Consciousness: Insights from Diffusion Tensor Imaging and Machine Learning — Human Brain Mapping (2016)

Mapping neural representations of heading direction and environmental context during imagined navigation of learned virtual environments

Authors: Nicco Reggente., Essoe, J.K., Jevtic, I., Rissman, J.

Abstract for CNS 2016 in New York, NY: Constructing a rich egocentric representation of one’s movement about an environment is a multi-faceted effort requiring a vast interplay across cortical areas responsible for visual processing, heading direction, and spatial coding. While electrophysiological recordings in rodents have identified robust neural correlates related to distinct aspects of navigation, experimental work with human subjects offers the unique potential to elucidate the mechanisms of navigational mental imagery, a process we frequently engage in when planning a route or giving directions. In the present study, we first familiarized participants with navigational paths about three highly distinctive virtual environments. The next day, while undergoing fMRI scanning, participants viewed a series of first-person videos that indicated either clockwise or counter-clockwise movement around the perimeter of each environment. After several rounds of video viewing, participants performed a new task in which they were covertly cued to imagine themselves walking along each of these same routes. We leveraged support vector machines within a searchlight-mapping approach to identify brain regions whose BOLD patterns coded for information pertaining to the participants’ heading direction or environmental context. As anticipated, many visual association regions with significant accuracy for decoding the contents of perceived navigation were also capable of decoding imagined navigation, although imagery classification performance was generally less robust. Interestingly, several frontal and temporal lobe regions showed decoding effects that were specific to mental imagery, and the distribution of these areas differed as a function of gender, potentially indicative of a qualitatively different mental representation of navigational information across males and females.

The full poster can be seen here: Reggente_et_al_CNS_Final

Shared and distinct contributions of rostrolateral prefrontal cortex to analogical reasoning and episodic memory retrieval

Andrew Westphal, Nicco Reggente, Kaori Ito, Jesse Rissman

Abstract: Rostrolateral prefrontal cortex (RLPFC) is widely appreciated to support higher cognitive functions, including analogical reasoning and episodic memory retrieval. However, these tasks have typically been studied in isolation, and thus it is unclear whether they involve common or distinct RLPFC mechanisms. Here, we introduce a novel functional magnetic resonance imaging (fMRI) task paradigm to compare brain activity during reasoning and memory tasks while holding bottom-up perceptual stimulation and response demands constant. Univariate analyses on fMRI data from twenty participants identified a large swath of left lateral prefrontal cortex, including RLPFC, that showed common engagement on reasoning trials with valid analogies and memory trials with accurately retrieved source details. Despite broadly overlapping recruitment, multi-voxel activity patterns within left RLPFC reliably differentiated these two trial types, highlighting the presence of at least partially distinct information processing modes. Functional connectivity analyses demonstrated that while left RLPFC showed consistent coupling with the fronto-parietal control network across tasks, its coupling with other cortical areas varied in a task-dependent manner. During the memory task, this region strengthened its connectivity with the default mode and memory retrieval networks, whereas during the reasoning task it coupled more strongly with a nearby left prefrontal region (BA 45) associated with semantic processing, as well as with a superior parietal region associated with visuospatial processing. Taken together, these data suggest a domain-general role for left RLPFC in monitoring and/or integrating task-relevant knowledge representations and showcase how its function cannot solely be attributed to episodic memory or analogical reasoning computations.

Read the full article, here: Westphal_HBM_2015