Nader Nikbakht

Integrating multimodal data is essential to advance neuroscience as a discipline. Large-scale collaborative efforts, exemplified by the BRAIN Initiative, together with advances in single-cell and spatial omics, multimodal imaging, human genetics, behavioral phenotyping, protein structure prediction, and related technologies, are transforming neuroscience into a data-rich, highly interconnected science. As experimental resources, scientific literature, and collaborative networks continue to expand, integrating discoveries across modalities, species, and levels of biological organization has become the field's central bottleneck. This Perspective argues that artificial intelligence (AI) is becoming essential for overcoming these constraints. Using six evolving approaches we outline strategies to accelerate AI adoption through community building and pilot projects that drive AI transformation at both the organizational and technological levels. Organizational transformation cultivates broad AI awareness and a pro-AI culture while technological transformation improves the efficiency, scalability, and quality of data analysis, allowing researchers to generate insights more rapidly and effectively. Together, these advances position AI as a key driver for advancing neuroscience at scale.

Recent studies examine the behavioral capacities of rats and mice with and without visual input, and the neuronal mechanisms underlying such capacities. These animals are assumed to be functionally blind under red light, an assumption that might originate in the fact that they are dichromats who possess ultraviolet and green cones, but not red cones. But the inability to see red as a color does not necessarily rule out form vision based on red light absorption. We measured Long-Evans rats’ capacity for visual form discrimination under red light of various wavelength bands. Upon viewing a black and white grating, they had to distinguish between two categories of orientation: horizontal and vertical. Psychometric curves plotting judged orientation versus angle demonstrate the conserved visual capacity of rats under red light. Investigations aiming to explore rodent physiological and behavioral functions in the absence of visual input should not assume red-light blindness.

Recent studies examine the behavioral capacities of rats and mice with and without visual input, and the neuronal mechanisms underlying such capacities. These animals are assumed to be functionally blind under red light, an assumption that might originate in the fact that they are dichromats who possess ultraviolet and green but not red cones. But the inability to see red as a color does not necessarily rule out form vision based on red light absorption. We measured Long-Evans rats’ capacity for visual form discrimination under red light of various wavelength bands. Upon viewing a black and white grating, they had to distinguish between two categories of orientation, horizontal and vertical. Psychometric curves plotting judged orientation versus angle demonstrate the conserved visual capacity of rats under red light. Investigations aiming to explore rodent physiological and behavioral functions in the absence of visual input should not assume red-light blindness.

We experience the world by constantly integrating cues from multiple modalities to form unified sensory percepts. Once familiar with multimodal properties of an object, we can recognize it regardless of the modality involved. In this chapter we will examine the case of a visual–tactile orientation categorization experiment in rats. We will explore the involvement of the cerebral cortex in recognizing objects through multiple sensory modalities. In the orientation categorization task, rats learned to examine and judge the orientation of a raised, black and white grating using touch, vision, or both. Their multisensory performance was better than the predictions of linear models for cue combination, indicating synergy between the two sensory channels. Neural recordings made from a candidate associative cortical area, the posterior parietal cortex (PPC), reflected the principal neuronal correlates of the behavioral results: PPC neurons encoded both graded information about the object and categorical information about the animal’s decision. Intriguingly single neurons showed identical responses under each of the three modality conditions providing a substrate for a neural circuit in the cortex that is involved in modality-invariant processing of objects. Keywords Multimodal integration Psychophysics Vision Touch Rat Linearity Bayesian Mutual information Posterior parietal cortex Neuronal coding