Evolutionary neuroscience: Are the brains of birds and mammals really so different?

Multimodality in the Collicular Pathway: Towards Compensatory Visual Processes

The integration of multisensory inputs plays a crucial role in shaping perception and behavior, particularly in the visual system. The collicular pathway, encompassing the optic tectum in non-mammalian vertebrates and the superior colliculus (SC) in mammals, is a key hub for integrating sensory information and mediating adaptive motor responses. Comparative studies across species reveal evolutionary adaptations that enhance sensory processing and contribute to compensatory mechanisms following neuronal injury. The present review outlines the structure and function of the multisensory visual pathways, emphasizing the retinocollicular projections, and their multisensory integration, which depends on synaptic convergence of afferents conveying information from different sensory modalities. The cellular mechanisms underlying multimodal integration remain to be fully clarified, and further investigations are needed to clarify the link between neuronal activity in response to multisensory stimulation and behavioral response involving motor activity. By exploring the interplay between fundamental neuroscience and translational applications, we aim to address multisensory integration as a pivotal target for its potential role in visual rehabilitation strategies.

Noise intensity modulates the responses of mantled howler monkeys to anthropophony

Anthropogenic noise is a major global pollutant but its effects on primates are poorly understood, limiting our ability to develop mitigation actions that favor their welfare and conservation. In this study, we used an experimental approach to determine the impact of variation in noise intensity on mantled howler monkeys (Alouatta palliata). We conducted the study at Los Tuxtlas (México), where we studied the physiological stress (proxied via fecal glucocorticoid metabolites, fGCM) and behavioral responses of 16 males. We played back chainsaw noise at two intensities (40 and 80 dB) and used days in which groups were not exposed to noise as matched controls. With increased noise intensity fGCM increased, vigilance and vocalizations were longer, and vigilance, vocalizations, and flight occurred quicker. Physiological and behavioral responses occurred even after low-intensity noise playbacks (i.e., 40 dB). Therefore, noise intensity is a significant factor explaining the responses of mantled howler monkeys to anthropogenic noise. These results imply that management actions aimed at eradicating anthropogenic noise are required for the conservation and welfare of mantled howler monkeys at Los Tuxtlas.

From Analog to Digital Computing: Is Homo sapiens’ Brain on Its Way to Become a Turing Machine?

The abstract basis of modern computation is the formal description of a finite state machine, the Universal Turing Machine, based on manipulation of integers and logic symbols. In this contribution to the discourse on the computer-brain analogy, we discuss the extent to which analog computing, as performed by the mammalian brain, is like and unlike the digital computing of Universal Turing Machines. We begin with ordinary reality being a permanent dialog between continuous and discontinuous worlds. So it is with computing, which can be analog or digital, and is often mixed. The theory behind computers is essentially digital, but efficient simulations of phenomena can be performed by analog devices; indeed, any physical calculation requires implementation in the physical world and is therefore analog to some extent, despite being based on abstract logic and arithmetic. The mammalian brain, comprised of neuronal networks, functions as an analog device and has given rise to artificial neural networks that are implemented as digital algorithms but function as analog models would. Analog constructs compute with the implementation of a variety of feedback and feedforward loops. In contrast, digital algorithms allow the implementation of recursive processes that enable them to generate unparalleled emergent properties. We briefly illustrate how the cortical organization of neurons can integrate signals and make predictions analogically. While we conclude that brains are not digital computers, we speculate on the recent implementation of human writing in the brain as a possible digital path that slowly evolves the brain into a genuine (slow) Turing machine.