Temporal integration of narrative information in a hippocampal amnesic patient

Zuo, Xiaoye; Honey, Christopher J.; Barense, Morgan D.; Crombie, Davide; Norman, Kenneth A.; Hasson, Uri; Chen, Janice

doi:10.1016/j.neuroimage.2020.116658

Cited by 23 publications

(15 citation statements)

References 42 publications

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“…The theory of hierarchical timescales in the cerebral cortex is influential across cognitive, systems, and clinical neuroscience (Baldassano et al, 2017;Burt et al, 2018;Chaudhuri et al, 2015;Chen et al, 2016;Cocchi et al, 2016;Demirtaş et al, 2019;Fuster, 1997;Hasson et al, 2008Hasson et al, , 2015Himberger et al, 2018;Kiebel et al, 2008;Murray et al, 2014;Runyan et al, 2017;Scott et al, 2017;Simony et al, 2016;Wasmuht et al, 2018;Watanabe et al, 2019;Yeshurun et al, 2017;Zuo et al, 2020). The intrinsic timescales of brain dynamics are longer in higher-order areas, as shown by single-unit data in macaques (E) HLI simulation of rSI DE:CE predicts longer alignment time at higher stages of processing.…”

Section: Discussionmentioning

confidence: 96%

“…We quantify the similarity by correlating the pattern of voxel activation at each time point (Figure 2A). Similar to the inter-subject correlation (ISC) analysis which provides a measure of the temporal reliability of the responses to complex stimuli (Hasson et al, 2004), the ISPC analysis provides a measure of the spatial reliability of the response to the stimuli at each time point (see also Zuo et al, 2020). The ISPC method differs from conventional fMRI data analysis methods in that it circumvents the need to specify a model for the neuronal processes in any given brain region during story listening.…”

Section: Empirical Measurements Of Context Dependence Temporal Alignmmentioning

confidence: 99%

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Constructing and Forgetting Temporal Context in the Human Cerebral Cortex

Chien

Honey

2020

Neuron

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Constructing and Forgetting Temporal Context in the Human Cerebral Cortex Highlights d Distinct cortical responses when the same stimulus is preceded by different contexts d Responses align as common input continues: sensory cortex, then higher-order cortex d Cortical regions maintain a distributed and hierarchical representation of context d Distributed cortical memory is gated and prior context can be flexibly forgotten

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Section: Discussionmentioning

confidence: 96%

Section: Empirical Measurements Of Context Dependence Temporal Alignmmentioning

confidence: 99%

Constructing and Forgetting Temporal Context in the Human Cerebral Cortex

Chien

Honey

2020

Neuron

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“…Specifically, hippocampal multivoxel patterns diverged gradually as the narratives unfolded (Milivojevic, Varadinov, Grabovetsky, Collin, & Doeller, 2016). Notably, regions of the default network can integrate narrative information on timescales of around 30 sec, even when the hippocampus is severely damaged (Zuo et al, 2020). However, successful memory encoding and retrieval of event sequences might require interactions with the hippocampus.…”

Section: Pattern Correlations Reflect Sequence Informationmentioning

confidence: 99%

“…We have highlighted contributions of the hippocampus and the adjacent entorhinal cortex to sequence memory. Notably, the hippocampal-entorhinal system supports episodic memory in close connection with cortical networks, which can integrate episodic information from the past 30 sec even when the hippocampus is damaged (Zuo et al, 2020). How temporal integration processes in cortical areas interact with the hippocampal-entorhinal region to create sequence memories remains to be understood.…”

Section: Outstanding Questionsmentioning

confidence: 99%

Sequence Memory in the Hippocampal–Entorhinal Region

Bellmund

Polti

Doeller

2020

Journal of Cognitive Neuroscience

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Episodic memories are constructed from sequences of events. When recalling such a memory, we not only recall individual events, but we also retrieve information about how the sequence of events unfolded. Here, we focus on the role of the hippocampal–entorhinal region in processing and remembering sequences of events, which are thought to be stored in relational networks. We summarize evidence that temporal relations are a central organizational principle for memories in the hippocampus. Importantly, we incorporate novel insights from recent studies about the role of the adjacent entorhinal cortex in sequence memory. In rodents, the lateral entorhinal subregion carries temporal information during ongoing behavior. The human homologue is recruited during memory recall where its representations reflect the temporal relationships between events encountered in a sequence. We further introduce the idea that the hippocampal–entorhinal region might enable temporal scaling of sequence representations. Flexible changes of sequence progression speed could underlie the traversal of episodic memories and mental simulations at different paces. In conclusion, we describe how the entorhinal cortex and hippocampus contribute to remembering event sequences—a core component of episodic memory.

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“…For instance, early neural recordings focused on anesthetized animals, but the transition to experiments with awake, behaving animals transformed our knowledge of sensory, motor, and cognitive brain functions [23][24][25][26][27]. More recently, researchers have moved towards using natural auditory and visual stimuli, finding novel neural responses not seen with artificial stimuli [28][29][30][31][32][33]; moreover, features of natural stimuli often better explain the observed variance in neural activity [34,35]. In human neuroscience and be-havior, advances in technology have enabled an expanded focus on a variety of mobile outdoor paradigms [36][37][38][39][40], spatial navigation tasks within immersive virtual environments [41,42], and tasks involving active social interactions [43][44][45][46].…”

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confidence: 99%

Behavioral and Neural Variability of Naturalistic Arm Movements

Peterson

Singh

Wang

et al. 2020

Preprint

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Motor behaviors are central to many functions and dysfunctions of the brain, and understanding their neural basis has consequently been a major focus in neuroscience. However, most studies of motor behaviors have been restricted to artificial, repetitive paradigms, far removed from natural movements performed "in the wild." Here, we leveraged recent advances in machine learning and computer vision to analyze intracranial recordings from 12 human subjects during thousands of spontaneous arm reach movements, observed over several days for each subject. These naturalistic movements elicited cortical spectral power patterns consistent with findings from controlled paradigms, but with an important difference: there was considerable neural variability across subjects and events. We modeled inter-event variability using ten behavioral and environmental features; the most important features explaining this variability were reach angle and recording day. Our work is among the first studies connecting behavioral and neural variability across cortex in humans during spontaneous movements and contributes to our understanding of long-term naturalistic behavior.

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Temporal integration of narrative information in a hippocampal amnesic patient

Cited by 23 publications

References 42 publications

Constructing and Forgetting Temporal Context in the Human Cerebral Cortex

Constructing and Forgetting Temporal Context in the Human Cerebral Cortex

Sequence Memory in the Hippocampal–Entorhinal Region

Behavioral and Neural Variability of Naturalistic Arm Movements

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