Snn Multimodal Brain

---
name: snn-multimodal-brain
description: "Brain-Inspired Multimodal Spiking Neural Network for Image-Text Retrieval. Activation: braininspired, multimodal, spiking, imagetext, retrieval"
---

# Brain-Inspired Multimodal Spiking Neural Network for Image-Text Retrieval

## Overview

Spiking neural networks (SNNs) have recently shown strong potential in unimodal visual and textual tasks, yet building a directly trained, low-energy, and high-performance SNN for multimodal applications such as image-text retrieval (ITR) remains highly challenging. Existing artificial neural network (ANN)-based methods often pursue richer unimodal semantics using deeper and more complex architectures, while overlooking cross-modal interaction, retrieval latency, and energy efficiency. To address these limitations, we present a brain-inspired Cross-Modal Spike Fusion network (CMSF) and apply it to ITR for the first time. The proposed spike fusion mechanism integrates unimodal features at the spike level, generating enhanced multimodal representations that act as soft supervisory signals to refine unimodal spike embeddings, effectively mitigating semantic loss within CMSF. Despite requiring only two time steps, CMSF achieves top-tier retrieval accuracy, surpassing state-of-the-art ANN counterparts while maintaining exceptionally low energy consumption and high retrieval speed. This work marks a significant step toward multimodal SNNs, offering a brain-inspired framework that unifies temporal dynamics with cross-modal alignment and provides new insights for future spiking-based multimodal research. The code is available at this https URL.

## Source

- **Paper:** Brain-Inspired Multimodal Spiking Neural Network for Image-Text Retrieval
- **Authors:** Xintao Zong, Xian Zhong, Wenxuan Liu, Jianhao Ding, Zhaofei Yu, Tiejun Huang
- **arXiv:** https://arxiv.org/abs/2603.26787v1
- **Published:** 2026-03-25
- **Category:** cs.CV

## Key Concepts

- **SNN - Brain-inspired neural networks using discrete spikes**
- **Multimodal - Integration of multiple data types (e.g., image + text)**

## Practical Applications

- **Brain Mapping**: Functional network construction from neuroimaging data
- **Disease Analysis**: Understanding neurological disorders through network patterns
- **Personalized Medicine**: Individual-specific brain function modeling
- **Cognitive Assessment**: Quantitative analysis of cognitive states


## Limitations

- Paper is a preprint (not peer-reviewed)
- Implementation details may require further validation
- Experimental results are subject to reproduction

## Activation Keywords

- braininspired
- multimodal
- spiking
- imagetext
- retrieval

## References

Xintao Zong, Xian Zhong, Wenxuan Liu, Jianhao Ding, Zhaofei Yu, Tiejun Huang. "Brain-Inspired Multimodal Spiking Neural Network for Image-Text Retrieval". arXiv preprint arXiv:2603.26787v1, 2026.