Back

Adapting to loss: A normative account of grief

Dulberg, Z.; Dubey, R.; Cohen, J. D.

2024-02-09 neuroscience
10.1101/2024.02.06.578702 bioRxiv
Show abstract

Grief is a reaction to loss that is observed across human cultures and even in other species. While the particular expressions of grief vary significantly, universal aspects include experiences of emotional pain and frequent remembering of what was lost. Despite its prevalence, and its obvious nature, considering grief from a normative perspective is puzzling: Why do we grieve? Why is it painful? And why is it sometimes prolonged enough to be clinically impairing? Using the framework of reinforcement learning with memory replay, we offer answers to these questions and suggest, counter-intuitively, that grief may have normative value with respect to reward maximization.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
PLOS Computational Biology
1863 papers in training set
Top 0.9%
22.5%
2
Computational Psychiatry
12 papers in training set
Top 0.1%
13.0%
3
eLife
5828 papers in training set
Top 16%
6.9%
4
Psychological Review
19 papers in training set
Top 0.1%
6.9%
5
Scientific Reports
3612 papers in training set
Top 32%
3.3%
50% of probability mass above
6
Neural Computation
39 papers in training set
Top 0.3%
2.5%
7
Frontiers in Psychiatry
87 papers in training set
Top 0.8%
2.5%
8
Nature Communications
5641 papers in training set
Top 39%
2.5%
9
Nature Human Behaviour
95 papers in training set
Top 0.8%
2.4%
10
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 21%
2.4%
11
Frontiers in Computational Neuroscience
60 papers in training set
Top 0.6%
2.2%
12
Addiction Neuroscience
17 papers in training set
Top 0.2%
2.0%
13
NeuroImage
903 papers in training set
Top 4%
2.0%
14
Network Neuroscience
126 papers in training set
Top 0.8%
1.8%
15
Frontiers in Behavioral Neuroscience
49 papers in training set
Top 0.5%
1.7%
16
Cognitive, Affective, & Behavioral Neuroscience
25 papers in training set
Top 0.2%
1.5%
17
Journal of Neurophysiology
302 papers in training set
Top 2%
1.4%
18
PLOS ONE
5266 papers in training set
Top 52%
1.4%
19
The Journal of Neuroscience
1025 papers in training set
Top 9%
1.1%
20
Neural Networks
35 papers in training set
Top 0.5%
1.1%
21
Frontiers in Artificial Intelligence
20 papers in training set
Top 0.6%
1.1%
22
Journal of The Royal Society Interface
235 papers in training set
Top 4%
1.0%
23
iScience
1154 papers in training set
Top 30%
1.0%
24
eneuro
439 papers in training set
Top 7%
1.0%
25
Biological Psychology
21 papers in training set
Top 0.4%
0.9%
26
Royal Society Open Science
214 papers in training set
Top 7%
0.6%
27
Frontiers in Neuroscience
256 papers in training set
Top 7%
0.6%
28
Mathematical Biosciences
49 papers in training set
Top 1%
0.6%
29
Biological Cybernetics
15 papers in training set
Top 0.3%
0.6%