scholarly journals Neural Correlates of Subsequent Memory-Related Gaze Reinstatement

2021 ◽  
pp. 1-15
Author(s):  
Jordana S. Wynn ◽  
Zhong-Xu Liu ◽  
Jennifer D. Ryan
Keyword(s):  
Eye Movements ◽  
Recognition Memory ◽  
Visual Processing ◽  
Memory Task ◽  
Neural Correlates ◽  
Brain Regions ◽  
Oculomotor Control ◽  
Related Activity ◽  
Pattern Similarity ◽  
Occipital Pole

Abstract Mounting evidence linking gaze reinstatement—the recapitulation of encoding-related gaze patterns during retrieval—to behavioral measures of memory suggests that eye movements play an important role in mnemonic processing. Yet, the nature of the gaze scanpath, including its informational content and neural correlates, has remained in question. In this study, we examined eye movement and neural data from a recognition memory task to further elucidate the behavioral and neural bases of functional gaze reinstatement. Consistent with previous work, gaze reinstatement during retrieval of freely viewed scene images was greater than chance and predictive of recognition memory performance. Gaze reinstatement was also associated with viewing of informationally salient image regions at encoding, suggesting that scanpaths may encode and contain high-level scene content. At the brain level, gaze reinstatement was predicted by encoding-related activity in the occipital pole and BG, neural regions associated with visual processing and oculomotor control. Finally, cross-voxel brain pattern similarity analysis revealed overlapping subsequent memory and subsequent gaze reinstatement modulation effects in the parahippocampal place area and hippocampus, in addition to the occipital pole and BG. Together, these findings suggest that encoding-related activity in brain regions associated with scene processing, oculomotor control, and memory supports the formation, and subsequent recapitulation, of functional scanpaths. More broadly, these findings lend support to scanpath theory's assertion that eye movements both encode, and are themselves embedded in, mnemonic representations.

scholarly journals Neural correlates of subsequent memory-related gaze reinstatement

2021 ◽  
Author(s):  
Jordana S. Wynn ◽  
Zhong-Xu Liu ◽  
Jennifer D. Ryan
Keyword(s):  
Eye Movements ◽  
Basal Ganglia ◽  
Recognition Memory ◽  
Visual Processing ◽  
Memory Task ◽  
Neural Correlates ◽  
Oculomotor Control ◽  
Related Activity ◽  
Pattern Similarity ◽  
Occipital Pole

AbstractMounting evidence linking gaze reinstatement- the recapitulation of encoding-related gaze patterns during retrieval- to behavioral measures of memory suggests that eye movements play an important role in mnemonic processing. Yet, the nature of the gaze scanpath, including its informational content and neural correlates, has remained in question. In the present study, we examined eye movement and neural data from a recognition memory task to further elucidate the behavioral and neural bases of functional gaze reinstatement. Consistent with previous work, gaze reinstatement during retrieval of freely-viewed scene images was greater than chance and predictive of recognition memory performance. Gaze reinstatement was also associated with viewing of informationally salient image regions at encoding, suggesting that scanpaths may encode and contain high-level scene content. At the brain level, gaze reinstatement was predicted by encoding-related activity in the occipital pole and basal ganglia, neural regions associated with visual processing and oculomotor control. Finally, cross-voxel brain pattern similarity analysis revealed overlapping subsequent memory and subsequent gaze reinstatement modulation effects in the parahippocampal place area and hippocampus, in addition to the occipital pole and basal ganglia. Together, these findings suggest that encoding-related activity in brain regions associated with scene processing, oculomotor control, and memory supports the formation, and subsequent recapitulation, of functional scanpaths. More broadly, these findings lend support to Scanpath Theory’s assertion that eye movements both encode, and are themselves embedded in, mnemonic representations.

The Effect of Bilateral Eye Movements on Emotional Face Recognition Memory Task

2014 ◽  
Vol 53 (5) ◽  
pp. 293 ◽  
Author(s):  
Na-Hyun Lee ◽  
Seung-Jun Kim ◽  
Ji-Woong Kim ◽  
Woo-Young Im ◽  
Hyukchan Kwon ◽  
...  
Keyword(s):  
Face Recognition ◽  
Eye Movements ◽  
Recognition Memory ◽  
Memory Task ◽  
Recognition Memory Task ◽  
Emotional Face

scholarly journals Unrestricted eye movements strengthen causal connectivity from hippocampal to oculomotor regions during scene construction

2021 ◽  
Author(s):  
Natalia Ladyka-Wojcik ◽  
Zhong-Xu Liu ◽  
Jennifer D. Ryan
Keyword(s):  
Eye Movements ◽  
Visual Processing ◽  
Oculomotor System ◽  
Visual Input ◽  
Causal Modeling ◽  
Oculomotor Control ◽  
Visual Stream ◽  
Functional Connections ◽  
Free Viewing ◽  
Scene Construction

Scene construction is a key component of memory recall, navigation, and future imagining, and relies on the medial temporal lobes (MTL). A parallel body of work suggests that eye movements may enable the imagination and construction of scenes, even in the absence of external visual input. There are vast structural and functional connections between regions of the MTL and those of the oculomotor system. However, the directionality of connections between the MTL and oculomotor control regions, and how it relates to scene construction, has not been studied directly in human neuroimaging. In the current study, we used dynamic causal modeling (DCM) to investigate this relationship at a mechanistic level using a scene construction task in which participants' eye movements were either restricted (fixed-viewing) or unrestricted (free-viewing). By omitting external visual input, and by contrasting free- versus fixed- viewing, the directionality of neural connectivity during scene construction could be determined. As opposed to when eye movements were restricted, allowing free viewing during construction of scenes strengthened top-down connections from the MTL to the frontal eye fields, and to lower-level cortical visual processing regions, suppressed bottom-up connections along the visual stream, and enhanced vividness of the constructed scenes. Taken together, these findings provide novel, non-invasive evidence for the causal architecture between the MTL memory system and oculomotor system associated with constructing vivid mental representations of scenes.

scholarly journals Dynamic connectivity analyses of intracranial EEG during recognition memory reveal various large-scale functional networks

2020 ◽  
Author(s):  
Jakub Kopal ◽  
Jaroslav Hlinka ◽  
Elodie Despouy ◽  
Luc Valton ◽  
Marie Denuelle ◽  
...  
Keyword(s):  
Recognition Memory ◽  
Large Scale ◽  
Visual Recognition ◽  
Effective Connectivity ◽  
Memory Task ◽  
Brain Regions ◽  
Neural Basis ◽  
Intracranial Eeg ◽  
Large Scale Networks ◽  
The Right

Recognition memory is the ability to recognize previously encountered events, objects, or people. It is characterized by its robustness and rapidness. Even this relatively simple ability requires the coordinated activity of a surprisingly large number of brain regions. These spatially distributed, but functionally linked regions are interconnected into large-scale networks. Understanding memory requires an examination of the involvement of these networks and the interactions between different regions while memory processes unfold. However, little is known about the dynamical organization of large-scale networks during the early phases of recognition memory. We recorded intracranial EEG, which affords high temporal and spatial resolution, while epileptic subjects performed a visual recognition memory task. We analyzed dynamic functional and effective connectivity as well as network properties. Various networks were identified, each with its specific characteristics regarding information flow (feedforward or feedback), dynamics, topology, and stability. The first network mainly involved the right visual ventral stream and bilateral frontal regions. It was characterized by early predominant feedforward activity, modular topology, and high stability. It was followed by the involvement of a second network, mainly in the left hemisphere, but notably also involving the right hippocampus, characterized by later feedback activity, integrated topology, and lower stability. The transition between networks was associated with a change in network topology. Overall, these results confirm that several large-scale brain networks, each with specific properties and temporal manifestation, are involved during recognition memory. Ultimately, understanding how the brain dynamically faces rapid changes in cognitive demand is vital to our comprehension of the neural basis of cognition.

scholarly journals The locus of recognition memory signals in human cortex depends on the complexity of the memory representations

2021 ◽  
Author(s):  
D. Merika W. Sanders ◽  
Rosemary A. Cowell
Keyword(s):  
Recognition Memory ◽  
Medial Temporal Lobe ◽  
Declarative Memory ◽  
Memory Task ◽  
Representational Content ◽  
Brain Regions ◽  
Complex Stimuli ◽  
Memory Representations ◽  
Memory Signals ◽  
Feature Memory

Representational theories predict that brain regions contribute to cognition according to the information they represent (e.g., simple versus complex), contradicting the traditional notion that brain regions are specialized for cognitive functions (e.g., perception versus memory). In support of representational accounts, substantial evidence now attests that the Medial Temporal Lobe (MTL) is not specialized solely for long-term declarative memory, but underpins other functions including perception and future-imagining for complex stimuli and events. However, a complementary prediction has been less well explored, namely that the cortical locus of declarative memory may fall outside the MTL if the to-be-remembered content is sufficiently simple. Specifically, the locus should coincide with the optimal neural code for the representations being retrieved. To test this prediction, we manipulated the complexity of the to-be-remembered representations in a recognition memory task. First, participants in the scanner viewed novel 3D objects and scenes, and we used multivariate analyses to identify regions in the ventral visual-MTL pathway that preferentially coded for either simple features of the stimuli, or complex conjunctions of those features. Next, in a separate scan, we tested recognition memory for these stimuli and performed neuroimaging contrasts that revealed two memory signals ‒ feature memory and conjunction memory. Feature memory signals were found in visual cortex, while conjunction memory signals emerged in MTL. Further, the regions optimally representing features via preferential feature-coding coincided with those exhibiting feature memory signals. These findings suggest that representational content, rather than cognitive function, is the primary organizing principle in the ventral visual-MTL pathway.

Cognitive distortions in an acutely traumatized sample: an investigation of predictive power and neural correlates

2011 ◽  
Vol 41 (10) ◽  
pp. 2149-2157 ◽  
Author(s):  
J. K. Daniels ◽  
K. Hegadoren ◽  
N. J. Coupland ◽  
B. H. Rowe ◽  
R. W. J. Neufeld ◽  
...  
Keyword(s):  
Symptom Severity ◽  
Visual Processing ◽  
Cognitive Distortions ◽  
Neural Correlates ◽  
Blood Oxygen Level Dependent ◽  
Brain Regions ◽  
Initial Symptom ◽  
Post Traumatic Stress ◽  
Diagnostic Status ◽  
Ptsd Severity

BackgroundCurrent theories of post-traumatic stress disorder (PTSD) place considerable emphasis on the role cognitive distortions such as self-blame, hopelessness or preoccupation with danger play in the etiology and maintenance of the disorder. Previous studies have shown that cognitive distortions in the early aftermath of traumatic events can predict future PTSD severity but, to date, no studies have investigated the neural correlates of this association.MethodWe conducted a prospective study with 106 acutely traumatized subjects, assessing symptom severity at three time points within the first 3 months post-trauma. A subsample of 20 subjects additionally underwent a functional 4-T magnetic resonance imaging (MRI) scan at 2 to 4 months post-trauma.ResultsCognitive distortions proved to be a significant predictor of concurrent symptom severity in addition to diagnostic status, but did not predict future symptom severity or diagnostic status over and above the initial symptom severity. Cognitive distortions were correlated with blood oxygen level-dependent (BOLD) signal strength in brain regions previously implicated in visual processing, imagery and autobiographic memory recall. Intrusion characteristics accounted for most of these correlations.ConclusionsThis investigation revealed significant predictive value of cognitive distortions concerning concurrent PTSD severity and also established a significant relationship between cognitive distortions and neural activations during trauma recall in an acutely traumatized sample. These data indicate a direct link between the extent of cognitive distortions and the intrusive nature of trauma memories.

Memory Networks Supporting Retrieval Effort and Retrieval Success Under Conditions of Full and Divided Attention

2009 ◽  
Vol 56 (6) ◽  
pp. 386-396 ◽  
Author(s):  
Erin I. Skinner ◽  
Myra A. Fernandes ◽  
Cheryl L. Grady
Keyword(s):  
Multivariate Analysis ◽  
Recognition Memory ◽  
Divided Attention ◽  
Brain Activity ◽  
Memory Performance ◽  
Memory Task ◽  
Brain Regions ◽  
Analysis Technique ◽  
The Right ◽  
Performance Results

We used a multivariate analysis technique, partial least squares (PLS), to identify distributed patterns of brain activity associated with retrieval effort and retrieval success. Participants performed a recognition memory task under full attention (FA) or two different divided attention (DA) conditions during retrieval. Behaviorally, recognition was disrupted when a word, but not digit-based distracting task, was performed concurrently with retrieval. PLS was used to identify patterns of brain activation that together covaried with the three memory conditions and which were functionally connected with activity in the right hippocampus to produce successful memory performance. Results indicate that activity in the right dorsolateral frontal cortex increases during conditions of DA at retrieval, and that successful memory performance in the DA-digit condition is associated with activation of the same network of brain regions functionally connected to the right hippocampus, as under FA, which increases with increasing memory performance. Finally, DA conditions that disrupt successful memory performance (DA-word) interfere with recruitment of both retrieval-effort and retrieval-success networks.

scholarly journals Brain Activity-Based Metrics for Assessing Learning States in VR under Stress among Firefighters: An Explorative Machine Learning Approach in Neuroergonomics

2021 ◽  
Vol 11 (7) ◽  
pp. 885
Author(s):  
Maher Abujelala ◽  
Rohith Karthikeyan ◽  
Oshin Tyagi ◽  
Jing Du ◽  
Ranjana K. Mehta
Keyword(s):  
Machine Learning ◽  
Environmental Conditions ◽  
Brain Activity ◽  
Memory Task ◽  
Classification Problem ◽  
Brain Regions ◽  
Training Data ◽  
Information Encoding ◽  
Machine Learning Approach ◽  
Encoding And Retrieval

The nature of firefighters` duties requires them to work for long periods under unfavorable conditions. To perform their jobs effectively, they are required to endure long hours of extensive, stressful training. Creating such training environments is very expensive and it is difficult to guarantee trainees’ safety. In this study, firefighters are trained in a virtual environment that includes virtual perturbations such as fires, alarms, and smoke. The objective of this paper is to use machine learning methods to discern encoding and retrieval states in firefighters during a visuospatial episodic memory task and explore which regions of the brain provide suitable signals to solve this classification problem. Our results show that the Random Forest algorithm could be used to distinguish between information encoding and retrieval using features extracted from fNIRS data. Our algorithm achieved an F-1 score of 0.844 and an accuracy of 79.10% if the training and testing data are obtained at similar environmental conditions. However, the algorithm’s performance dropped to an F-1 score of 0.723 and accuracy of 60.61% when evaluated on data collected under different environmental conditions than the training data. We also found that if the training and evaluation data were recorded under the same environmental conditions, the RPM, LDLPFC, RDLPFC were the most relevant brain regions under non-stressful, stressful, and a mix of stressful and non-stressful conditions, respectively.

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