The field of cognitive robotics and multimodal intelligence is witnessing a significant shift towards more embodied and spatially-aware approaches. Researchers are exploring the role of morphology and spatial cognition in intelligent behavior, moving beyond traditional neural network-based models. This direction is driven by the need for more adaptive, generalizable, and efficient solutions for real-world applications. Noteworthy papers in this area include: Morphological Cognition: Classifying MNIST Digits Through Morphological Computation Alone, which demonstrates image classification without neural circuitry. MaRVL-QA: A Benchmark for Mathematical Reasoning over Visual Landscapes, which introduces a new benchmark for evaluating mathematical reasoning skills in multimodal large language models. From reactive to cognitive: brain-inspired spatial intelligence for embodied agents, which presents a unified framework for constructing and leveraging structured spatial memory in embodied agents. Mimicking associative learning of rats via a neuromorphic robot in open field maze using spatial cell models, which explores the emulation of associative learning in rodents using neuromorphic robots. 11Plus-Bench: Demystifying Multimodal LLM Spatial Reasoning with Cognitive-Inspired Analysis, which introduces a systematic evaluation framework to assess the spatial reasoning abilities of state-of-the-art multimodal large language models.