Human Hippocampal Dynamics during Response Conflict

Oehrn, Carina R.; Baumann, Christin; Fell, Juergen; Lee, Hweeling; Kessler, Henrik; Habel, Ute; Hanslmayr, Simon; Axmacher, Nikolai

doi:10.1016/j.cub.2015.07.032

Cited by 37 publications

(28 citation statements)

References 28 publications

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“…Interestingly, in our dataset, hippocampal responses are only seen when a token appeared to create behavioral conflict, but not at the trial start when all features of the situation were already signaled. This may indicate that the hippocampus is specifically involved in monitoring behavioral conflict, including a retrieval of threat memory (Oehrn et al, 2015; Ito and Lee, 2016). …”

Section: Discussionmentioning

confidence: 99%

Dissecting the Function of Hippocampal Oscillations in a Human Anxiety Model

et al. 2017

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Neural oscillations in hippocampus and medial prefrontal cortex (mPFC) are a hallmark of rodent anxiety models that build on conflict between approach and avoidance. Yet, the function of these oscillations, and their expression in humans, remain elusive. Here, we used magnetoencephalography (MEG) to investigate neural oscillations in a task that simulated approach–avoidance conflict, wherein 23 male and female human participants collected monetary tokens under a threat of virtual predation. Probability of threat was signaled by color and learned beforehand by direct experience. Magnitude of threat corresponded to a possible monetary loss, signaled as a quantity. We focused our analyses on an a priori defined region-of-interest, the bilateral hippocampus. Oscillatory power under conflict was linearly predicted by threat probability in a location consistent with right mid-hippocampus. This pattern was specific to the hippocampus, most pronounced in the gamma band, and not explained by spatial movement or anxiety-like behavior. Gamma power was modulated by slower theta rhythms, and this theta modulation increased with threat probability. Furthermore, theta oscillations in the same location showed greater synchrony with mPFC theta with increased threat probability. Strikingly, these findings were not seen in relation to an increase in threat magnitude, which was explicitly signaled as a quantity and induced similar behavioral responses as learned threat probability. Thus, our findings suggest that the expression of hippocampal and mPFC oscillatory activity in the context of anxiety is specifically linked to threat memory. These findings resonate with neurocomputational accounts of the role played by hippocampal oscillations in memory.SIGNIFICANCE STATEMENT We use a biologically relevant approach–avoidance conflict test in humans while recording neural oscillations with magnetoencephalography to investigate the expression and function of hippocampal oscillations in human anxiety. Extending nonhuman studies, we can assign a possible function to hippocampal oscillations in this task, namely threat memory communication. This blends into recent attempts to elucidate the role of brain synchronization in defensive responses to threat.

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Section: Discussionmentioning

confidence: 99%

Dissecting the Function of Hippocampal Oscillations in a Human Anxiety Model

et al. 2017

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“…1 in Oehrn et al (2014)). Importantly, theta burst responses induced by conflict have been recorded in human hippocampus (Oehrn et al, 2015). Moreover, midline frontal EEG theta is induced by memory as well as conflict paradigms (Hsieh and Ranganath, 2014).…”

Section: Discussionmentioning

confidence: 99%

Frequency-specific electrophysiologic correlates of resting state fMRI networks

Hacker¹,

Snyder²,

Pahwa³

et al. 2017

NeuroImage

144

107

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Resting state functional MRI (R-fMRI) studies have shown that slow (< 0.1 Hz), intrinsic fluctuations of the blood oxygen level dependent (BOLD) signal are temporally correlated within hierarchically organized functional systems known as resting state networks (RSNs) (Doucet et al., 2011). Most broadly, this hierarchy exhibits a dichotomy between two opposed systems (Fox et al., 2005). One system engages with the environment and includes the visual, auditory, and sensorimotor (SMN) networks as well as the dorsal attention network (DAN), which controls spatial attention. The other system includes the default mode network (DMN) and the fronto-parietal control system (FPC), RSNs that instantiate episodic memory and executive control, respectively. Here, we test the hypothesis, based on the spectral specificity of electrophysiologic responses to perceptual vs. memory tasks (Klimesch, 1999; Pfurtscheller and Lopes da Silva, 1999), that these two large-scale neural systems also manifest frequency specificity in the resting state. We measured the spatial correspondence between electrocorticographic (ECoG) band-limited power (BLP) and R-fMRI correlation patterns in awake, resting, human subjects. Our results show that, while gamma BLP correspondence was common throughout the brain, theta (4–8 Hz) BLP correspondence was stronger in the DMN and FPC, whereas alpha (8–12 Hz) correspondence was stronger in the SMN and DAN. Thus, the human brain, at rest, exhibits frequency specific electrophysiology, respecting both the spectral structure of task responses and the hierarchical organization of RSNs.

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“…This imbalance has resurfaced in computational models of memory (3), and later as the imbalance between pattern completion and pattern separation, processes linked to computational properties of subfields within the hippocampus (HC) (4)(5)(6). Understanding the developmental organization of HC subfields is therefore crucial to understand how associated changes in HC-subfield computations drive concomitant changes in learning and memory.…”

mentioning

confidence: 99%

Hippocampal maturity promotes memory distinctiveness in childhood and adolescence

Keresztes

Bender

Bodammer

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

118

158

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Adaptive learning systems need to meet two complementary and partially conflicting goals: detecting regularities in the world versus remembering specific events. The hippocampus (HC) keeps a fine balance between computations that extract commonalities of incoming information (i.e., pattern completion) and computations that enable encoding of highly similar events into unique representations (i.e., pattern separation). Histological evidence from young rhesus monkeys suggests that HC development is characterized by the differential development of intrahippocampal subfields and associated networks. However, due to challenges in the in vivo investigation of such developmental organization, the ontogenetic timing of HC subfield maturation remains controversial. Delineating its course is important, as it directly influences the fine balance between pattern separation and pattern completion operations and, thus, developmental changes in learning and memory. Here, we relate in vivo, high-resolution structural magnetic resonance imaging data of HC subfields to behavioral memory performance in children aged 6-14 y and in young adults. We identify a multivariate profile of age-related differences in intrahippocampal structures and show that HC maturity as captured by this pattern is associated with age differences in the differential encoding of unique memory representations.hippocampal subfields | episodic memory | specificity | pattern separation | child development M any years ago, the Swiss developmentalist Jean Piaget noted an imbalance between assimilation and accommodation during early and middle childhood in the sense that children tend to extract schematic knowledge at the expense of learning and recollecting specific events (1, 2). This imbalance has resurfaced in computational models of memory (3), and later as the imbalance between pattern completion and pattern separation, processes linked to computational properties of subfields within the hippocampus (HC) (4-6). Understanding the developmental organization of HC subfields is therefore crucial to understand how associated changes in HC-subfield computations drive concomitant changes in learning and memory.An important step toward unraveling controversies about human hippocampal maturation (7,8) is to acknowledge that the HC is not a homogeneous structure, but rather is composed of cytoarchitectonically and functionally distinct subfields (9). The availability of high-resolution, in vivo magnetic resonance imaging (MRI) of the HC permits the study of specific contributions of different HC subfields in humans (10-12). Computational and rodent models of HC function and high-resolution MRI studies in humans have sought to establish the contributions of individual HC subfields to specific mnemonic functions. For example, the dentate gyrus (DG) has been closely linked to pattern separation (6). Developmental findings from animal models (13) and initial evidence from human studies (14) suggest that the DG matures later than other HC subfields. Likewise, memory funct...

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Human Hippocampal Dynamics during Response Conflict

Cited by 37 publications

References 28 publications

Dissecting the Function of Hippocampal Oscillations in a Human Anxiety Model

Dissecting the Function of Hippocampal Oscillations in a Human Anxiety Model

Frequency-specific electrophysiologic correlates of resting state fMRI networks

Hippocampal maturity promotes memory distinctiveness in childhood and adolescence

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