# Neuropsychology of AI: Relationship Between Activation Proximity and Categorical Proximity Within Neural Categories of Synthetic Cognition

arXiv: https://arxiv.org/abs/2410.11868 · HTML: https://mlsanity.com/paper/2410.11868/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 61 references that are in the map.
- First posted on arXiv 8 Oct 2024.

## Builds on (most cited first, 8 of 8)

- [What Does BERT Look At? An Analysis of BERT's Attention](https://mlsanity.com/paper/1906.04341/) (2019)
- [Gradient Descent Finds Global Minima of Deep Neural Networks](https://mlsanity.com/paper/1811.03804/) (2018)
- [Explainability for Large Language Models: A Survey](https://mlsanity.com/paper/2309.01029/) (2023)
- [What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models](https://mlsanity.com/paper/1812.09355/) (2018)
- [Machine learning for neural decoding](https://mlsanity.com/paper/1708.00909/) (2017)
- [Evaluating Neuron Interpretation Methods of NLP Models](https://mlsanity.com/paper/2301.12608/) (2023)
- [Cosine Similarity Knowledge Distillation for Individual Class Information Transfer](https://mlsanity.com/paper/2311.14307/) (2023)
- [Psychology of Artificial Intelligence: Epistemological Markers of the Cognitive Analysis of Neural Networks](https://mlsanity.com/paper/2407.09563/) (2024)

## Built on by (most cited first, 3 of 3)

- [Synthetic Categorical Restructuring large Or How AIs Gradually Extract Efficient Regularities from Their Experience of the World](https://mlsanity.com/paper/2503.10643/) (2025)
- [Intra-neuronal attention within language models Relationships between activation and semantics](https://mlsanity.com/paper/2503.12992/) (2025)
- [Polysemy of Synthetic Neurons Towards a New Type of Explanatory Categorical Vector Spaces](https://mlsanity.com/paper/2505.07831/) (2025)

## Abstract (arXiv)

Neuropsychology of artificial intelligence focuses on synthetic neural cog nition as a new type of study object within cognitive psychology. With the goal of making artificial neural networks of language models more explainable, this approach involves transposing concepts from cognitive psychology to the interpretive construction of artificial neural cognition. The human cognitive concept involved here is categorization, serving as a heuristic for thinking about the process of segmentation and construction of reality carried out by the neural vectors of synthetic cognition.