representational similarity analysis
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Hippocampus ◽  
2022 ◽  
Author(s):  
Alireza Kazemi ◽  
Christine A. Coughlin ◽  
Dana M. DeMaster ◽  
Simona Ghetti

2021 ◽  
Author(s):  
Joana B Vieira ◽  
Andreas Olsson

Helping of conspecifics under threat has been observed across species. In humans, the dominant view proposes that empathy is the key proximal mechanism driving helping motivation in a threatening context, but little is known about how one s own defensive responses to the threat may guide helping decisions. In this pre-registered study, we manipulated threat imminence to activate the entire defensive brain circuitry, and assess the impact of different defensive responses on risky helping behaviour. Forty-nine participants underwent fMRI scanning while making trial-by-trial decisions about whether or not to help a co-participant avoid aversive shocks at the risk of receiving a shock themselves. Helping decisions were prompted under imminent and distal threat, based on the spatiotemporal distance to the administration of the shock to the co-participant. We found that greater engagement of reactive fear circuits (insula, ACC, PAG) during the threat presentation led to helping decisions, whereas engagement of cognitive fear circuits (hippocampus and vmPFC) preceded decisions not to help. Relying on representational similarity analysis, we identified how the defensive circuitry uniquely represented the threat to oneself, and the distress of the co-participant during the task. Importantly, we found that the strength with which the amygdala represented the threat to oneself, and not the other s distress, predicted decisions to help. Our results demonstrate that defensive neural circuits coordinating fast escape from immediate danger may also facilitate decisions to help others, potentially by engaging neurocognitive systems implicated in caregiving across mammals. Taken together, our findings provide novel insights into the proximal basis of altruistic responding, suggesting that defensive responses may play a more important role in helping than previously understood.


2021 ◽  
Vol 8 (11) ◽  
Author(s):  
Irem Undeger ◽  
Renée M. Visser ◽  
Nina Becker ◽  
Lieke de Boer ◽  
Armita Golkar ◽  
...  

Past research has shown that attributions of intentions to other's actions determine how we experience these actions and their consequences. Yet, it is unknown how such attributions affect our learning and memory. Addressing this question, we combined neuroimaging with an interactive threat learning paradigm in which two interaction partners (confederates) made choices that had either threatening (shock) or safe (no shock) consequences for the participants. Importantly, participants were led to believe that one partner intentionally caused the delivery of shock, whereas the other did not (i.e. unintentional partner). Following intentional versus unintentional shocks, participants reported an inflated number of shocks and a greater increase in anger and vengeance. We applied a model-based representational similarity analysis to blood-oxygen-level-dependent (BOLD)-MRI patterns during learning. Surprisingly, we did not find any effects of intentionality. The threat value of actions, however, was represented as a trial-by-trial increase in representational similarity in the insula and the inferior frontal gyrus. Our findings illustrate how neural pattern formation can be used to study a complex interaction.


2021 ◽  
Vol 12 ◽  
Author(s):  
Seth M. Levine ◽  
Jens V. Schwarzbach

Representational similarity analysis (RSA) is a popular multivariate analysis technique in cognitive neuroscience that uses functional neuroimaging to investigate the informational content encoded in brain activity. As RSA is increasingly being used to investigate more clinically-geared questions, the focus of such translational studies turns toward the importance of individual differences and their optimization within the experimental design. In this perspective, we focus on two design aspects: applying individual vs. averaged behavioral dissimilarity matrices to multiple participants' neuroimaging data and ensuring the congruency between tasks when measuring behavioral and neural representational spaces. Incorporating these methods permits the detection of individual differences in representational spaces and yields a better-defined transfer of information from representational spaces onto multivoxel patterns. Such design adaptations are prerequisites for optimal translation of RSA to the field of precision psychiatry.


2021 ◽  
Vol 21 (9) ◽  
pp. 2055
Author(s):  
Rohit S. Kamath ◽  
Kimberly B. Weldon ◽  
Hannah R. Moser ◽  
Philip C. Burton ◽  
Scott R. Sponheim ◽  
...  

2021 ◽  
Author(s):  
Huawei Xu ◽  
Ming Liu ◽  
Delong Zhang

Using deep neural networks (DNNs) as models to explore the biological brain is controversial, which is mainly due to the impenetrability of DNNs. Inspired by neural style transfer, we circumvented this problem by using deep features that were given a clear meaning--the representation of the semantic content of an image. Using encoding models and the representational similarity analysis, we quantitatively showed that the deep features which represented the semantic content of an image mainly modulated the activity of voxels in the early visual areas (V1, V2, and V3) and these features were essentially depictive but also propositional. This result is in line with the core viewpoint of the grounded cognition to some extent, which suggested that the representation of information in our brain is essentially depictive and can implement symbolic functions naturally.


2021 ◽  
Author(s):  
Xiongbo Wu ◽  
Xavier Viñals ◽  
Aya Ben-Yakov ◽  
Bernhard P. Staresina ◽  
Lluís Fuentemilla

AbstractMuch work in rodents and in humans has provided evidence that post-encoding reinstatement plays an important role in stabilizing memory beyond initial learning processes. However, it remains unclear whether memory reinstatement is important for the rapid - ‘one-shot’ - learning of an unfolding episode. Here, we asked whether the reinstatement of an episode may occur preferentially post-encoding, when an individual perceives a meaningful event to be concluded. We asked human participants (male and female) to encode sequences of pictures depicting unique episodic-like events. We used representational similarity analysis of scalp electroencephalography recordings during encoding and found evidence for memory reactivation of the just encoded sequence of elements at the offset of the episode. Importantly, memory reinstatement was not observed between successive elements within an episode, indicating memory reactivation was specifically induced once participants perceived the unfolding episode to be completed. We also found that memory reinstatement predicted memory recollection of an encoded episode and that offset memory reinstatement was not present when participants encoded sequences of pictures that were not perceived as meaningful episodes. These results indicate that memory reinstatement at episode offsets is a mechanism selectively engaged to support rapid memory formation of single events.


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