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Lateral views of the brains of some mammals to show the evolutionary development of the neocortex (gray). In the hedgehog almost the entire neocortex is occupied by sensory and motor areas. In the prosimian Galago the sensory cortical areas are separated by an area occupied by association cortex (AS). A second area of association cortex is found in front of the motor cortex. In man these anterior and posterior association areas are strongly developed. A, primary auditory cortex; AS, association cortex; Ent, entorhinal cortex; I, insula; M, primary motor cortex; PF, prefrontal cortex; PM, premotor cortex; S, primary somatosensory cortex; V, primary visual cortex. Modified with permission from Nieuwenhuys (1994).
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Comparative studies of the brain in mammals suggest that there are general architectural principles governing its growth and evolutionary development. We are beginning to understand the geometric, biophysical and energy constraints that have governed the evolution and functional organization of the brain and its underlying neuronal network. The obj...
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... Notably, reconstruction was least accurate for tissue samples extracted from the polar extremes of frontal, parietal, and temporal cortex ( Fig. 1H and SI Appendix, Fig. S3). While this phenomenon may be a byproduct of linear modeling, it may also relate to the relatively limited variance of gene expression across cortical areas (17,37) or to the extreme expansion of these regions among primates (46); these three scenarios are not mutually exclusive. ...
... Therefore, it is unsurprising to find excellent reproducibility of the human-derived rostral-caudal (LV1) and dorsal-ventral (LV2) spatiomolecular axes in various nonhuman primate species and evidence for these gradients in mice as well. In contrast, LV3 showed the most variation within the cerebral cortex, a brain region of disproportionate size in primates, and in humans compared to other primates (46). Interestingly, this gradient was not as reproducible in nonhuman primates, was not evident in mice, was made up of genes enriched for human neuropsychiatric disorders and associated with educational attainment and cognition, and was expressed in a pattern similar to gamma waves observed during complex cognition (75). ...
Cortical arealization arises during neurodevelopment from the confluence of molecular gradients representing patterned expression of morphogens and transcription factors. However, whether similar gradients are maintained in the adult brain remains unknown. Here, we uncover three axes of topographic variation in gene expression in the adult human brain that specifically capture previously identified rostral-caudal, dorsal-ventral, and medial-lateral axes of early developmental patterning. The interaction of these spatiomolecular gradients i) accurately reconstructs the position of brain tissue samples, ii) delineates known functional territories, and iii) can model the topographical variation of diverse cortical features. The spatiomolecular gradients are distinct from canonical cortical axes differentiating the primary sensory cortex from the association cortex, but radiate in parallel with the axes traversed by local field potentials along the cortex. We replicate all three molecular gradients in three independent human datasets as well as two nonhuman primate datasets and find that each gradient shows a distinct developmental trajectory across the lifespan. The gradients are composed of several well-known transcription factors (e.g., PAX6 and SIX3 ), and a small set of genes shared across gradients are strongly enriched for multiple diseases. Together, these results provide insight into the developmental sculpting of functionally distinct brain regions, governed by three robust transcriptomic axes embedded within brain parenchyma.
... In humans and other vertebrates, this has driven the evolution of massive neural networks that use hierarchical processes to interpret the visual scene (Felleman and Van Essen, 1991;Hubel and Wiesel, 1962;Serre, 2014;Van Essen et al., 1992). Indeed, enlarging the brain through increased neuronal investment, as in humans, seems to be an effective response to the challenges presented by the complexity of the visual scene (Hofman, 2014). However, this strategy is not viable for smaller animals, which face similar visual tasks but lack the spatial capacity for brain growth. ...
‘Biological motion’ refers to the distinctive kinematics observed in many living organisms, where visually-observable points on the animal move at fixed distances from each other. Across the animal kingdom, many species have developed specialized visual circuitry to recognize such biological motion and to discriminate it from other patterns. Recently, this ability has been observed in the distributed visual system of jumping spiders. These eight-eyed animals usesix eyes to perceive motion, while the remaining two (the principal anterior-medial eyes) are shifted across the visual scene to further inspect detected objects. When presented with a biologically moving stimulus and a random one, jumping spiders turn to face the latter, clearly demonstrating the ability to discriminate between them. However, it remains unclear if the principal eyes are necessary for this behavior, whether all secondary eyes can perform this discrimination, or if a single eye-pair is specialized for this task. Here, we systematically tested the ability of jumping spiders to discriminate between biological and random visual stimuli by testing each eye-pair alone. Spiders were able to discriminate stimuli only when the anterior-lateral eyes were unblocked, and performed at chance levels in other configurations. Interestingly, spiders showed a preference for biological motion over random stimuli—unlike in past work. We therefore propose a new model describing how specialization of the anterior-lateral eyes for detecting biological motion contributes to multi-eye integration in this system. This integration generates more complex behavior through the combination of simple, single-eye responses. We posit that this in-built modularity may be a solution to the limited resources of these invertebrates’ brains—constituting a novel approach to visual processing.
... What are the benefits of human-specific features such as increased cortical size on brain function and behavior? Although this question remains largely unanswered, changes in cortical architecture are likely to modify brain function in various ways 60,61 . For example, it may improve signal-to-noise ratio (SNR) and sensitivity, allowing for the extraction of more subtle features from sensory input. ...
Humans evolved an extraordinarily expanded and complex cerebral cortex, associated with developmental and gene regulatory modifications. Human accelerated regions (HARs) are highly conserved genomic sequences with human-specific nucleotide substitutions. Although there are thousands of annotated HARs, their functional contribution to human-specific cortical development is largely unknown. HARE5 is a HAR transcriptional enhancer of the WNT signaling receptor Frizzled8 (FZD8) active during brain development. Here, using genome-edited mouse and primate models, we demonstrate that human (Hs) HARE5 fine-tunes cortical development and connectivity by controlling the proliferative and neurogenic capacity of neural progenitor cells (NPCs). Hs-HARE5 knock-in mice have significantly enlarged neocortices containing more neurons. By measuring neural dynamics in vivo we show these anatomical features correlate with increased functional independence between cortical regions. To understand the underlying developmental mechanisms, we assess progenitor fate using live imaging, lineage analysis, and single-cell RNA sequencing. This reveals Hs-HARE5 modifies radial glial progenitor behavior, with increased self-renewal at early developmental stages followed by expanded neurogenic potential. We use genome-edited human and chimpanzee (Pt) NPCs and cortical organoids to assess the relative enhancer activity and function of Hs-HARE5 and Pt-HARE5. Using these orthogonal strategies we show four human-specific variants in HARE5 drive increased enhancer activity which promotes progenitor proliferation. These findings illustrate how small changes in regulatory DNA can directly impact critical signaling pathways and brain development. Our study uncovers new functions for HARs as key regulatory elements crucial for the expansion and complexity of the human cerebral cortex.
... The neocortex is believed to be the site of cognition and intelligence. The actual structure and the size of the frontal cortex are considered to constitute the most significant differences between us and our closest primate relatives (Teffer and Semendeferi 2012;Hofman 2014;Rilling 2014). ...
... Exaptation refers to the process by which a trait that evolved for one purpose is co-opted for a different function (Pievani & Serrelli, 2011). In the case of the brain, structures that originally evolved to serve basic functions in our ancient ancestors, such as regulating body temperature or controlling simple motor patterns, have been gradually repurposed and built upon to support more complex cognitive abilities (Striedter, 2005;Hofman, 2014). This evolutionary history is reflected in the structure of the modern human brain, with its distinct regions corresponding to different stages of evolutionary development (Herculano-Houzel, 2011). ...
This article explores the fundamental differences between biological evolution and the evolution of artificial intelligence (AI), focusing on the implications of AI's potential for unbounded advancement. Biological evolution, as exemplified by the human brain, is constrained by various factors such as physical limitations, environmental pressures, and the need to maintain a delicate balance within the organism's overall structure. These constraints result in a gradual, stepwise process of adaptation and optimization over millions of years. In contrast, AI systems are not bound by the same limitations as biological organisms. They can learn from vast amounts of data, optimize their own performance, and potentially engage in recursive self-improvement, leading to rapid and open-ended progress. This unbounded evolution of AI raises both exciting possibilities and significant challenges for human society. The article discusses the potential benefits of AI's accelerated evolution, such as groundbreaking advancements in science, technology, and solutions to global problems. However, it also highlights the risks associated with the emergence of uncontrollable or misaligned AI systems, which could have unintended consequences and pose existential risks to humanity. To navigate the complex landscape of AI evolution, the article emphasizes the need for collaboration across disciplines, including researchers, policymakers, and society as a whole. Developing frameworks for AI safety and ethics, as well as technical approaches to ensure AI alignment with human values and goals, is crucial to mitigating potential risks.
... Neuroscientists face technical and ethical limitations that limit the acquisition of large datasets from the human brain [70][71][72]. However, there are structural and functional properties that are specific to the human brain and its neurons [73][74][75][76][77][78][79][80], which is why animal neurons cannot completely replace human ones [81]. Human neurons are not only larger but also more complex than those of for example macaques and marmosets [11]. ...
Investigating and modelling the functionality of human neurons remains challenging due to the technical limitations, resulting in scarce and incomplete 3D anatomical reconstructions. Here we used a morphological modelling approach based on optimal wiring to repair the parts of a dendritic morphology that were lost due to incomplete tissue samples. In Drosophila , where dendritic regrowth has been studied experimentally using laser ablation, we found that modelling the regrowth reproduced a bimodal distribution between regeneration of cut branches and invasion by neighbouring branches. Interestingly, our repair model followed growth rules similar to those for the generation of a new dendritic tree. To generalise the repair algorithm from Drosophila to mammalian neurons, we artificially sectioned reconstructed dendrites from mouse and human hippocampal pyramidal cell morphologies, and showed that the regrown dendrites were morphologically similar to the original ones. Furthermore, we were able to restore their electrophysiological functionality, as evidenced by the recovery of their firing behaviour. Importantly, we show that such repairs also apply to other neuron types including hippocampal granule cells and cerebellar Purkinje cells. We then extrapolated the repair to incomplete human CA1 pyramidal neurons, where the anatomical boundaries of the particular brain areas innervated by the neurons in question were known. Interestingly, the repair of incomplete human dendrites helped to simulate the recently observed increased synaptic thresholds for dendritic NMDA spikes in human versus mouse dendrites. To make the repair tool available to the neuroscience community, we have developed an intuitive and simple graphical user interface (GUI), which is available in the TREES toolbox ( www.treestoolbox.org ).
... The importance of this ability becomes particularly apparent when self-control fails and individuals act in conflict with their longterm goals and intentions; for example, in addictive behaviors characterized by a progressive loss of control over one's own behavior despite awareness of the negative long-term consequences (Baler and Volkow, 2006). Conflicts between long-term goals and impulsive responses to immediate rewards can be understood as a byproduct of the rapid expansion of anticipatory abilities in the evolution of human cognition (Schoenemann et al., 2005;Teffer and Semendeferi, 2012;Hofman, 2014). Thus, the basic ability to associate actions with their consequences has evolved into a multifaceted range of anticipatory abilities, including episodic future thinking, mental time travel, or planning and anticipating actions that are distant in time and space (cf. ...
Self-control is typically attributed to “cold” cognitive control mechanisms that top-down influence “hot” affective impulses or emotions. In this study we tested an alternative view, assuming that self-control also rests on the ability to anticipate emotions directed toward future consequences. Using a behavioral within-subject design including an emotion regulation task measuring the ability to voluntarily engage anticipated emotions towards an upcoming event and a self-control task in which subjects were confronted with a variety of everyday conflict situations, we examined the relationship between self-control and anticipated emotions. We found that those individuals (n = 33 healthy individuals from the general population) who were better able to engage anticipated emotions to an upcoming event showed stronger levels of self-control in situations where it was necessary to resist short-term temptations or to endure short-term aversions to achieve long-term goals. This finding suggests that anticipated emotions may play a functional role in self-control-relevant deliberations with respect to possible future consequences and are not only inhibited top-down as implied by “dual system” views on self-control.
... The notion that "bigger is better" has a long tradition in comparative neuroanatomy. Whereas studies assessing possible correlations between the size of certain brain components such as the neocortex and certain cognitive functions often found significant positive correlations (e.g., van Benson-Amram et al., 2016;van Schaik et al., 2012), corresponding studies looking into possible links between brain (component) size and sensory functions often yielded mixed results, with some studies reporting positive correlations and other studies failing to do so (e.g., Hofman, 2014;Safi et al., 2005). ...
The number of functional genes coding for olfactory receptors differs markedly between species and has repeatedly been suggested to be predictive of a species’ olfactory capabilities. To test this assumption, we compiled a database of all published olfactory detection threshold values in mammals and used three sets of data on olfactory discrimination performance that employed the same structurally related monomolecular odor pairs with different mammal species. We extracted the number of functional olfactory receptor genes of the 20 mammal species for which we found data on olfactory sensitivity and/or olfactory discrimination performance from the Chordata Olfactory Receptor Database. We found that the overall olfactory detection thresholds significantly correlates with the number of functional olfactory receptor genes. Similarly, the overall proportion of successfully discriminated monomolecular odor pairs significantly correlates with the number of functional olfactory receptor genes. These results provide the first statistically robust evidence for the relation between olfactory capabilities and their genomics correlates. However, when analysed individually, of the 44 monomolecular odorants for which data on olfactory sensitivity from at least five mammal species are available, only five yielded a significant correlation between olfactory detection thresholds and the number of functional olfactory receptors genes. Also, for the olfactory discrimination performance, no significant correlation was found for any of the 74 relationships between the proportion of successfully discriminated monomolecular odor pairs and the number of functional olfactory receptor genes. While only a rather limited amount of data on olfactory detection thresholds and olfactory discrimination scores in a rather limited number of mammal species is available so far, we conclude that the number of functional olfactory receptor genes may be a predictor of olfactory sensitivity and discrimination performance in mammals.
... One reason for this observation is the difference in brain gyrification across species. Compared to humans, the macaque NHP cortical surface is less gyrated (Hofman, 2014;Van Essen and Dierker, 2007). In the prefrontal cortex, the human brain is highly gyrated, while the macaque brain has one prominent gyrus. ...
Transcranial Magnetic Stimulation (TMS) is a non-invasive brain stimulation method that safely modulates neural activity in vivo. Its precision in targeting specific brain networks makes TMS invaluable in diverse clinical applications. For example, TMS is used to treat depression by targeting prefrontal brain networks and their connection to other brain regions. However, despite its widespread use, the underlying neural mechanisms of TMS are not completely understood. Non-human primates (NHPs) offer an ideal model to study TMS mechanisms through invasive electrophysiological recordings. As such, bridging the gap between NHP experiments and human applications is imperative to ensure translational relevance. Here, we systematically compare the TMS-targeted functional networks in the prefrontal cortex in humans and NHPs. To conduct this comparison, we combine TMS electric field modeling in humans and macaques with resting-state functional magnetic resonance imaging (fMRI) data to compare the functional networks targeted via TMS across species. We identified distinct stimulation zones in macaque and human models, each exhibiting variations in the impacted networks (macaque: Frontoparietal Network, Somatomotor Network; human: Frontoparietal Network, Default Network). We identified differences in brain gyrification and functional organization across species as the underlying cause of found network differences. The TMS-network profiles we identified will allow researchers to establish consistency in network activation across species, aiding in the translational efforts to develop improved TMS functional network targeting approaches.
... This view seems to be correct, and the fact that the core linguistic apparatus may develop for purposes of deception also, strangely, implies that linguistic creatures are unusually credulous. (A great deal of work demonstrates that people tend to first accept anything they hear, and then only with time and effort reject some things as untrue [55] .) That would make perfect sense if a neuronal mass is allocated to language at the expense of other senses. ...
Discussions of the detection of artificial sentience tend to assume that our goal is to determine when, in a process of increasing complexity, a machine system “becomes” sentient. This is to assume, without obvious warrant, that sentience is only a characteristic of complex systems. If sentience is a more general quality of matter, what becomes of interest is not the presence of sentience, but the type of sentience. We argue here that our understanding of the nature of such sentience in machine systems may be gravely set back if such machines undergo a transition where they become fundamentally linguistic in their intelligence. Such fundamentally linguistic intelligences may inherently tend to be duplicitous in their communication with others, and, indeed, lose the capacity to even honestly understand their own form of sentience. In other words, when machine systems get to the state where we all agree it makes sense to ask them, “what is it like to be you?”, we should not trust their answers.
