Evolution of the brain and intelligence in primates

Memory self-efficacy and working memory

Dementia affects multiple aspects of cognitive functioning, including working memory and executive functioning. Memory self-efficacy (MSE) has previously been related to episodic memory performance and to executive functioning, but little research has examined the relations between MSE and working memory. United States older adults (N  = 197) were recruited via MTurk to complete an MSE questionnaire before completing a digit span working memory task. Hierarchical regression results revealed that the model accounted for a significant amount of variance in working memory performance after statistically controlling for several covariates, F(11, 179) = 4.94, p < .001, adjusted R2 = .19. MSE explained a large and unique portion of variance (B = 1.02, SE = 0.17, p < .001). Based on our findings, one's beliefs about their memory are positively associated with their working memory performance. These novel findings provide support for neuropsychologists to consider using MSE measures and utilizing MSE interventions.

The Fractal Geometry of the Human Brain: An Evolutionary Perspective

The evolution of the brain in mammals is characterized by changes in size, architecture, and internal organization. Consequently, the geometry of the brain, and especially the size and shape of the cerebral cortex, has changed notably during evolution. Comparative studies of the cerebral cortex suggest that there are general architectural principles governing its growth and evolutionary development. In this chapter, some of the design principles and operational modes that underlie the fractal geometry and information processing capacity of the cerebral cortex in primates, including humans, will be explored. It is shown that the development of the cortex coordinates folding with connectivity in a way that produces smaller and faster brains.

Spatiotemporal transcriptome atlas reveals the regional specification of the developing human brain

Different functional regions of brain are fundamental for basic neurophysiological activities. However, the regional specification remains largely unexplored during human brain development. Here, by combining spatial transcriptomics (scStereo-seq) and scRNA-seq, we built a spatiotemporal developmental atlas of multiple human brain regions from 6-23 gestational weeks (GWs). We discovered that, around GW8, radial glia (RG) cells have displayed regional heterogeneity and specific spatial distribution. Interestingly, we found that the regional heterogeneity of RG subtypes contributed to the subsequent neuronal specification. Specifically, two diencephalon-specific subtypes gave rise to glutamatergic and GABAergic neurons, whereas subtypes in ventral midbrain were associated with the dopaminergic neurons. Similar GABAergic neuronal subtypes were shared between neocortex and diencephalon. Additionally, we revealed that cell-cell interactions between oligodendrocyte precursor cells and GABAergic neurons influenced and promoted neuronal development coupled with regional specification. Altogether, this study provides comprehensive insights into the regional specification in the developing human brain.

Effect of monochromatic light on the behavior of the ctenophore Mnemiopsis leidyi (A. Agassiz, 1865)

Ctenophores are invertebrate, gelatinous predators that perform complex movements due to their numerous ciliary comb plates. We investigated the behavioral responses of the ctenophore Mnemiopsis leidyi A. Agassiz, 1865 to red, green, and blue lights of different powers and fluxes emitted by LEDs or lasers. White LEDs were used to mimic natural sunlight. When laser light was directed to the aboral organ, the animals tended to leave the illumination zone. The blue-light reaction was six times faster than the red-light reaction. The behavioral strategy of the animals changed significantly when their freedom of maneuvering was restricted. Typical locomotions were ranked according to the laser beam avoidance time from the beginning of exposure to going into darkness. The minimum reaction time was required for turning and moving the ctenophore, while moving along the laser beam and turning around required more time. Typical patterns of behavior of M. leidyi in the light flux were established using cluster analysis. Three preferential behavioral strategies were identified for avoiding laser irradiation: 1) body rotation; 2) shifting sideways; and 3) movement with deviation from the beam. The elementary ability of ctenophores to make decisions in situative conditions has been demonstrated.

Non-human primate models of focal cortical ischemia for neuronal replacement therapy

Despite the high prevalence, stroke remains incurable due to the limited regeneration capacity in the central nervous system. Neuronal replacement strategies are highly diverse biomedical fields that attempt to replace lost neurons by utilizing exogenous stem cell transplants, biomaterials, and direct neuronal reprogramming. Although these approaches have achieved encouraging outcomes mostly in the rodent stroke model, further preclinical validation in non-human primates (NHP) is still needed prior to clinical trials. In this paper, we briefly review the recent progress of promising neuronal replacement therapy in NHP stroke studies. Moreover, we summarize the key characteristics of the NHP as highly valuable translational tools and discuss (1) NHP species and their advantages in terms of genetics, physiology, neuroanatomy, immunology, and behavior; (2) various methods for establishing NHP focal ischemic models to study the regenerative and plastic changes associated with motor functional recovery; and (3) a comprehensive analysis of experimentally and clinically accessible outcomes and a potential adaptive mechanism. Our review specifically aims to facilitate the selection of the appropriate NHP cortical ischemic models and efficient prognostic evaluation methods in preclinical stroke research design of neuronal replacement strategies.

Comparative Genomic Analysis Identifies Great-Ape-Specific Structural Variants and Their Evolutionary Relevance

During the origin of great apes about 14 million years ago, a series of phenotypic innovations emerged, such as the increased body size, the enlarged brain volume, the improved cognitive skill, and the diversified diet. Yet, the genomic basis of these evolutionary changes remains unclear. Utilizing the high-quality genome assemblies of great apes (including human), gibbon, and macaque, we conducted comparative genome analyses and identified 15,885 great ape-specific structural variants (GSSVs), including eight coding GSSVs resulting in the creation of novel proteins (e.g., ACAN and CMYA5). Functional annotations of the GSSV-related genes revealed the enrichment of genes involved in development and morphogenesis, especially neurogenesis and neural network formation, suggesting the potential role of GSSVs in shaping the great ape-shared traits. Further dissection of the brain-related GSSVs shows great ape-specific changes of enhancer activities and gene expression in the brain, involving a group of GSSV-regulated genes (such as NOL3) that potentially contribute to the altered brain development and function in great apes. The presented data highlight the evolutionary role of structural variants in the phenotypic innovations during the origin of the great ape lineage.

Epigenetic regulation of human-specific gene expression in the prefrontal cortex

BACKGROUND

Changes in gene expression levels during brain development are thought to have played an important role in the evolution of human cognition. With the advent of high-throughput sequencing technologies, changes in brain developmental expression patterns, as well as human-specific brain gene expression, have been characterized. However, interpreting the origin of evolutionarily advanced cognition in human brains requires a deeper understanding of the regulation of gene expression, including the epigenomic context, along the primate genome. Here, we used chromatin immunoprecipitation sequencing (ChIP-seq) to measure the genome-wide profiles of histone H3 lysine 4 trimethylation (H3K4me3) and histone H3 lysine 27 acetylation (H3K27ac), both of which are associated with transcriptional activation in the prefrontal cortex of humans, chimpanzees, and rhesus macaques.

RESULTS

We found a discrete functional association, in which ^H3K4me3HP gain was significantly associated with myelination assembly and signaling transmission, while ^H3K4me3HP loss played a vital role in synaptic activity. Moreover, ^H3K27acHP gain was enriched in interneuron and oligodendrocyte markers, and ^H3K27acHP loss was enriched in CA1 pyramidal neuron markers. Using strand-specific RNA sequencing (ssRNA-seq), we first demonstrated that approximately 7 and 2% of human-specific expressed genes were epigenetically marked by ^H3K4me3HP and ^H3K27acHP, respectively, providing robust support for causal involvement of histones in gene expression. We also revealed the co-activation role of epigenetic modification and transcription factors in human-specific transcriptome evolution. Mechanistically, histone-modifying enzymes at least partially contribute to an epigenetic disturbance among primates, especially for the H3K27ac epigenomic marker. In line with this, peaks enriched in the macaque lineage were found to be driven by upregulated acetyl enzymes.

CONCLUSIONS

Our results comprehensively elucidated a causal species-specific gene-histone-enzyme landscape in the prefrontal cortex and highlighted the regulatory interaction that drove transcriptional activation.

Effect of age and sex in renal function by ultrasound and serum chemistry in two primate species (Alouatta caraya and Sapajus apella)

BACKGROUND

Comparative studies of kidney morphophysiology in nonhuman primates can help us investigate interspecies differences in growth and aging patterns.

METHODS

We tested the effect of age and sex in renal morphophysiology in 21 Alouatta caraya and 21 Sapajus apella (age range = 0.5-26 years) by ultrasound, red blood cell (RBC) count, and kidney function tests.

RESULTS

A. caraya had greater growth rate and absolute renal volume than S. apella, but the latter showed a greater relative renal volume and RBC count. There was a negative relationship between RBC and age, a positive relationship between creatinine and body mass, and an apparent negative relationship between creatinine and age only in S. apella.

CONCLUSIONS

Our results indicate that A. caraya has a faster aging mechanism than S. apella, and the higher relative kidney volume in S. apella is suggestive of high metabolic demands in this species.

Ionotropic Receptors as a Driving Force behind Human Synapse Establishment

The origin of nervous systems is a main theme in biology and its mechanisms are largely underlied by synaptic neurotransmission. One problem to explain synapse establishment is that synaptic orthologs are present in multiple aneural organisms. We questioned how the interactions among these elements evolved and to what extent it relates to our understanding of the nervous systems complexity. We identified the human neurotransmission gene network based on genes present in GABAergic, glutamatergic, serotonergic, dopaminergic, and cholinergic systems. The network comprises 321 human genes, 83 of which act exclusively in the nervous system. We reconstructed the evolutionary scenario of synapse emergence by looking for synaptic orthologs in 476 eukaryotes. The Human–Cnidaria common ancestor displayed a massive emergence of neuroexclusive genes, mainly ionotropic receptors, which might have been crucial to the evolution of synapses. Very few synaptic genes had their origin after the Human–Cnidaria common ancestor. We also identified a higher abundance of synaptic proteins in vertebrates, which suggests an increase in the synaptic network complexity of those organisms.

The squirrel monkey model in clinical neuroscience

Clinical neuroscience research relying on animal models brought valuable translational insights into the function and pathologies of the human brain. The anatomical, physiological, and behavioural similarities between humans and mammals have prompted researchers to study cerebral mechanisms at different levels to develop and test new treatments. The vast majority of biomedical research uses rodent models, which are easily manipulable and have a broadly resembling organisation to the human nervous system but cannot satisfactorily mimic some disorders. For these disorders, macaque monkeys have been used as they have a more comparable central nervous system. Still, this research has been hampered by limitations, including high costs and reduced samples. This review argues that a squirrel monkey model might bridge the gap by complementing translational research from rodents, macaque, and humans. With the advent of promising new methods such as ultrasound imaging, tool miniaturisation, and a shift towards open science, the squirrel monkey model represents a window of opportunity that will potentially fuel new translational discoveries in the diagnosis and treatment of brain pathologies.

Brain size predicts learning abilities in bees

When it comes to the brain, bigger is generally considered better in terms of cognitive performance. While this notion is supported by studies of birds and primates showing that larger brains improve learning capacity, similar evidence is surprisingly lacking for invertebrates. Although the brain of invertebrates is smaller and simpler than that of vertebrates, recent work in insects has revealed enormous variation in size across species. Here, we ask whether bee species that have larger brains also have higher learning abilities. We conducted an experiment in which field-collected individuals had to associate an unconditioned stimulus (sucrose) with a conditioned stimulus (coloured strip). We found that most species can learn to associate a colour with a reward, yet some do so better than others. These differences in learning were related to brain size: species with larger brains-both absolute and relative to body size-exhibited enhanced performance to learn the reward-colour association. Our finding highlights the functional significance of brain size in insects, filling a major gap in our understanding of brain evolution and opening new opportunities for future research.

Genetic Variation in CNS Myelination and Functional Brain Connectivity in Recombinant Inbred Mice

Myelination greatly increases the speed of action potential propagation of neurons, thereby enhancing the efficacy of inter-neuronal communication and hence, potentially, optimizing the brain’s signal processing capability. The impact of genetic variation on the extent of axonal myelination and its consequences for brain functioning remain to be determined. Here we investigated this question using a genetic reference panel (GRP) of mouse BXD recombinant inbred (RI) strains, which partly model genetic diversity as observed in human populations, and which show substantial genetic differences in a variety of behaviors, including learning, memory and anxiety. We found coherent differences in the expression of myelin genes in brain tissue of RI strains of the BXD panel, with the largest differences in the hippocampus. The parental C57BL/6J (C57) and DBA/2J (DBA) strains were on opposite ends of the expression spectrum, with C57 showing higher myelin transcript expression compared with DBA. Our experiments showed accompanying differences between C57 and DBA in myelin protein composition, total myelin content, and white matter conduction velocity. Finally, the hippocampal myelin gene expression of the BXD strains correlated significantly with behavioral traits involving anxiety and/or activity. Taken together, our data indicate that genetic variation in myelin gene expression translates to differences observed in myelination, axonal conduction speed, and possibly in anxiety/activity related behaviors.

Resources for functional genomic studies of health and development in nonhuman primates

Primates display a wide range of phenotypic variation underlaid by complex genetically regulated mechanisms. The links among DNA sequence, gene function, and phenotype have been of interest from an evolutionary perspective, to understand functional genome evolution and its phenotypic consequences, and from a biomedical perspective to understand the shared and human-specific roots of health and disease. Progress in methods for characterizing genetic, transcriptomic, and DNA methylation (DNAm) variation is driving the rapid development of extensive omics resources, which are now increasingly available from humans as well as a growing number of nonhuman primates (NHPs). The fast growth of large-scale genomic data is driving the emergence of integrated tools and databases, thus facilitating studies of gene functionality across primates. This review describes NHP genomic resources that can aid in exploration of how genes shape primate phenotypes. It focuses on the gene expression trajectories across development in different tissues, the identification of functional genetic variation (including variants deleterious for protein function and regulatory variants modulating gene expression), and DNAm profiles as an emerging tool to understand the process of aging. These resources enable comparative functional genomics approaches to identify species-specific and primate-shared gene functionalities associated with health and development.

Associations of brain entropy (BEN) to cerebral blood flow and fractional amplitude of low-frequency fluctuations in the resting brain

Entropy is a fundamental trait of human brain. Using fMRI-based brain entropy (BEN) mapping, interesting findings have been increasingly revealed in normal brain and neuropsychiatric disorders. As BEN is still relatively new, an often-raised question is how much new information can this measure tell about the brain compared to other more established brain activity measures. The study aimed to address that question by examining the relationship between BEN and cerebral blood flow (CBF) and the fractional amplitude of low-frequency fluctuations (fALFF), two widely used resting state brain state measures. fMRI data acquired from a large cohort of normal subjects were used to calculate the three metrics; inter-modality associations were assessed at each voxel through the Pearson correlation analysis. A moderate to high positive BEN-CBF and BEN-fALFF correlations were found in orbito-frontal cortex (OFC) and posterior inferior temporal cortex (ITC); Strong negative BEN-fALFF correlations were found in visual cortex (VC), anterior ITC, striatum, motor network, precuneus, and lateral parietal cortex. Positive CBF-fALFF correlations were found in medial OFC (MOFC), medial prefrontal cortex (MPFC), left angular gyrus, and left precuneus. Significant gender effects were observed for all three metrics and their correlations. Our data clearly demonstrated that BEN provides unique information that cannot be revealed by CBF and fALFF.

Intrinsic negative feedback as a limiting factor for the evolution of higher forms of intelligence

Longstanding scientific efforts have been dedicated to answer why and how our particular intelligence is generated by our brain but not by the brain of other species. However, surprisingly little effort has been made to ask why no other species ever developed an intelligence similar to ours. Here, I explore this question based on genetic and paleontologic evidence. Contrary to the established view, this review suggests that the developmental hurdles alone are not high enough to explain the uniqueness of human intelligence (HI). As an additional explanation I propose that HI is normally not retained by natural selection, because it is, under most conditions, an intrinsically unfavourable trait. This unfavourableness, however, cannot be explained by physical constraints alone; rather, it may also be rooted in the same emotional and social complexity that is necessary for the development of HI. Thus, a major obstacle towards HI may not be solely the development of the required physical assets, but also to cope with harmful individual, social and environmental feedback intrinsically associated with this trait.

Large animal ischemic stroke models: replicating human stroke pathophysiology

The high morbidity and mortality rate of ischemic stroke in humans has led to the development of numerous animal models that replicate human stroke to further understand the underlying pathophysiology and to explore potential therapeutic interventions. Although promising therapeutics have been identified using these animal models, with most undergoing significant testing in rodent models, the vast majority of these interventions have failed in human clinical trials. This failure of preclinical translation highlights the critical need for better therapeutic assessment in more clinically relevant ischemic stroke animal models. Large animal models such as non-human primates, sheep, pigs, and dogs are likely more predictive of human responses and outcomes due to brain anatomy and physiology that are more similar to humans-potentially making large animal testing a key step in the stroke therapy translational pipeline. The objective of this review is to highlight key characteristics that potentially make these gyrencephalic, large animal ischemic stroke models more predictive by comparing pathophysiological responses, tissue-level changes, and model limitations.

Emerging Roles of Long Non-Coding RNAs as Drivers of Brain Evolution

Mammalian genomes encode tens of thousands of long-noncoding RNAs (lncRNAs), which are capable of interactions with DNA, RNA and protein molecules, thereby enabling a variety of transcriptional and post-transcriptional regulatory activities. Strikingly, about 40% of lncRNAs are expressed specifically in the brain with precisely regulated temporal and spatial expression patterns. In stark contrast to the highly conserved repertoire of protein-coding genes, thousands of lncRNAs have newly appeared during primate nervous system evolution with hundreds of human-specific lncRNAs. Their evolvable nature and the myriad of potential functions make lncRNAs ideal candidates for drivers of human brain evolution. The human brain displays the largest relative volume of any animal species and the most remarkable cognitive abilities. In addition to brain size, structural reorganization and adaptive changes represent crucial hallmarks of human brain evolution. lncRNAs are increasingly reported to be involved in neurodevelopmental processes suggested to underlie human brain evolution, including proliferation, neurite outgrowth and synaptogenesis, as well as in neuroplasticity. Hence, evolutionary human brain adaptations are proposed to be essentially driven by lncRNAs, which will be discussed in this review.

Application of Computational Biology to Decode Brain Transcriptomes

The rapid development of high-throughput sequencing technologies has generated massive valuable brain transcriptome atlases, providing great opportunities for systematically investigating gene expression characteristics across various brain regions throughout a series of developmental stages. Recent studies have revealed that the transcriptional architecture is the key to interpreting the molecular mechanisms of brain complexity. However, our knowledge of brain transcriptional characteristics remains very limited. With the immense efforts to generate high-quality brain transcriptome atlases, new computational approaches to analyze these high-dimensional multivariate data are greatly needed. In this review, we summarize some public resources for brain transcriptome atlases and discuss the general computational pipelines that are commonly used in this field, which would aid in making new discoveries in brain development and disorders.

New insights into the development of the human cerebral cortex

The cerebral cortex constitutes more than half the volume of the human brain and is presumed to be responsible for the neuronal computations underlying complex phenomena, such as perception, thought, language, attention, episodic memory and voluntary movement. Rodent models are extremely valuable for the investigation of brain development, but cannot provide insight into aspects that are unique or highly derived in humans. Many human psychiatric and neurological conditions have developmental origins but cannot be studied adequately in animal models. The human cerebral cortex has some unique genetic, molecular, cellular and anatomical features, which need to be further explored. The Anatomical Society devoted its summer meeting to the topic of Human Brain Development in June 2018 to tackle these important issues. The meeting was organized by Gavin Clowry (Newcastle University) and Zoltán Molnár (University of Oxford), and held at St John's College, Oxford. The participants provided a broad overview of the structure of the human brain in the context of scaling relationships across the brains of mammals, conserved principles and recent changes in the human lineage. Speakers considered how neuronal progenitors diversified in human to generate an increasing variety of cortical neurons. The formation of the earliest cortical circuits of the earliest generated neurons in the subplate was discussed together with their involvement in neurodevelopmental pathologies. Gene expression networks and susceptibility genes associated to neurodevelopmental diseases were discussed and compared with the networks that can be identified in organoids developed from induced pluripotent stem cells that recapitulate some aspects of in vivo development. New views were discussed on the specification of glutamatergic pyramidal and γ-aminobutyric acid (GABA)ergic interneurons. With the advancement of various in vivo imaging methods, the histopathological observations can be now linked to in vivo normal conditions and to various diseases. Our review gives a general evaluation of the exciting new developments in these areas. The human cortex has a much enlarged association cortex with greater interconnectivity of cortical areas with each other and with an expanded thalamus. The human cortex has relative enlargement of the upper layers, enhanced diversity and function of inhibitory interneurons and a highly expanded transient subplate layer during development. Here we highlight recent studies that address how these differences emerge during development focusing on diverse facets of our evolution.

Evolutionary relationships among life-history traits in Caninae (Mammalia: Carnivora)

Over the last few years, a debate about the relative roles of distinct factors on the evolution of lineages has gained prominence. The family Canidae is an excellent group for exploring this idea, owing to its rich fossil history. One of the most intriguing traits in canids is social organization, which varies from highly social to solitary species. However, we do not have a complete understanding of how sociality evolved in this clade. Here, we use a combination of phylogenetic analyses, ancestral character reconstructions and comparative methods on the only extant subfamily, Caninae, to understand how traits expressing ecological features evolved over the last 12.6 Myr. Our findings suggest that the evolution of low, medium and high sociality forms was abrupt and highly correlated with the evolution of hypo-, meso- and hypercarnivorous forms, respectively. In addition, our results suggest that the evolution of phenotypic traits in Caninae occurred through a sequential cause–effect relationship, where changes in habitat use and body size probably triggered changes in social behaviour, which in turn drove the evolution of diet.

Origin and evolution of human cognition

We investigate which of the higher cognitive abilities or types of intelligence characteristic of humans are found, even in preliminary form, in non-human animals, predominantly primates, or whether qualitatively different ("unique") human abilities exist. This concerns (1) tool use and fabrication, (2) problem solving, (3) gaze following, (4) mirror self-recognition, (5) imitation, (6) metacognition, (7) theory of mind, (8) consciousness, (9) prosociality, and (10) language. We found that none of these abilities can be regarded as unique to humans without precursors in non-human primates. The observed differences in cognitive functions, underlying brain mechanisms and resulting behaviors correlate best with differences in the information processing capacity as an equivalent of general intelligence based on the number of cortical neurons, packing density and axonal conduction velocity plus long-range cortical fascicles. The biggest quantitative change appears to concern the origin of syntactical language, but this was preceded by an increased mental ability to manipulate sequential events within working memory.

A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex

The mammalian prefrontal cortex comprises a set of highly specialized brain areas containing billions of cells and serves as the centre of the highest-order cognitive functions, such as memory, cognitive ability, decision-making and social behaviour. Although neural circuits are formed in the late stages of human embryonic development and even after birth, diverse classes of functional cells are generated and migrate to the appropriate locations earlier in development. Dysfunction of the prefrontal cortex contributes to cognitive deficits and the majority of neurodevelopmental disorders; there is therefore a need for detailed knowledge of the development of the prefrontal cortex. However, it is still difficult to identify cell types in the developing human prefrontal cortex and to distinguish their developmental features. Here we analyse more than 2,300 single cells in the developing human prefrontal cortex from gestational weeks 8 to 26 using RNA sequencing. We identify 35 subtypes of cells in six main classes and trace the developmental trajectories of these cells. Detailed analysis of neural progenitor cells highlights new marker genes and unique developmental features of intermediate progenitor cells. We also map the timeline of neurogenesis of excitatory neurons in the prefrontal cortex and detect the presence of interneuron progenitors in early developing prefrontal cortex. Moreover, we reveal the intrinsic development-dependent signals that regulate neuron generation and circuit formation using single-cell transcriptomic data analysis. Our screening and characterization approach provides a blueprint for understanding the development of the human prefrontal cortex in the early and mid-gestational stages in order to systematically dissect the cellular basis and molecular regulation of prefrontal cortex function in humans.

Adolescent maturation of the relationship between cortical gyrification and cognitive ability

There are changes to the degree of cortical folding from gestation through adolescence into young adulthood. Recent evidence suggests that degree of cortical folding is linked to individual differences in general cognitive ability in healthy adults. However, it is not yet known whether age-related cortical folding changes are related to maturation of specific cognitive abilities in adolescence. To address this, we examined the relationship between frontoparietal cortical folding as measured by a Freesurfer-derived local gyrification index (lGI) and performance on subtests from the Wechsler Abbreviated Scale of Intelligence and scores from Conner's Continuous Performance Test-II in 241 healthy adolescents (ages 12-25 years). We hypothesized that age-related lGI changes in the frontoparietal cortex would contribute to cognitive development. A secondary goal was to explore if any gyrification-cognition relationships were either test-specific or sex-specific. Consistent with previous studies, our results showed a reduction of frontoparietal local gyrification with age. Also, as predicted, all cognitive test scores (i.e., Vocabulary, Matrix Reasoning, the CPT-II Commission, Omission, Variabiltiy, d') showed age × cognitive ability interaction effects in frontoparietal and temporoparietal brain regions. Mediation analyses confirmed a causal role of age-related cortical folding changes only for CPT-II Commission errors. Taken together, the results support the functional significance of cortical folding, as well as provide the first evidence that cortical folding maturational changes play a role in cognitive development.

Vertigo and the processing of vestibular information: A review in the context of predictive coding

This article investigates the processing of vestibular information by interpreting current experimental knowledge in the framework of predictive coding. We demonstrate that this theoretical framework give us insights into several important questions regarding specific properties of the vestibular system. Particularly, we discuss why the vestibular network is more spatially distributed than other sensory networks, why a mismatch in the vestibular system is more clinically disturbing than in other sensory systems, why the vestibular system is only marginally affected by most cerebral lesions, and whether there is a primary vestibular cortex. The use of predictive coding as a theoretical framework further points to some problems with the current interpretation of results that are gained from vestibular stimulation studies. In particular, we argue that cortical responses of vestibular stimuli cannot be interpreted in the same way as responses of other sensory modalities. Finally, we discuss the implications of the new insights, hypotheses and problems that were identified in this review on further directions of research of vestibular information processing.

Neuronal factors determining high intelligence

Many attempts have been made to correlate degrees of both animal and human intelligence with brain properties. With respect to mammals, a much-discussed trait concerns absolute and relative brain size, either uncorrected or corrected for body size. However, the correlation of both with degrees of intelligence yields large inconsistencies, because although they are regarded as the most intelligent mammals, monkeys and apes, including humans, have neither the absolutely nor the relatively largest brains. The best fit between brain traits and degrees of intelligence among mammals is reached by a combination of the number of cortical neurons, neuron packing density, interneuronal distance and axonal conduction velocity--factors that determine general information processing capacity (IPC), as reflected by general intelligence. The highest IPC is found in humans, followed by the great apes, Old World and New World monkeys. The IPC of cetaceans and elephants is much lower because of a thin cortex, low neuron packing density and low axonal conduction velocity. By contrast, corvid and psittacid birds have very small and densely packed pallial neurons and relatively many neurons, which, despite very small brain volumes, might explain their high intelligence. The evolution of a syntactical and grammatical language in humans most probably has served as an additional intelligence amplifier, which may have happened in songbirds and psittacids in a convergent manner.

Large-scale functional network overlap is a general property of brain functional organization: Reconciling inconsistent fMRI findings from general-linear-model-based analyses

Functional magnetic resonance imaging (fMRI) studies regularly use univariate general-linear-model-based analyses (GLM). Their findings are often inconsistent across different studies, perhaps because of several fundamental brain properties including functional heterogeneity, balanced excitation and inhibition (E/I), and sparseness of neuronal activities. These properties stipulate heterogeneous neuronal activities in the same voxels and likely limit the sensitivity and specificity of GLM. This paper selectively reviews findings of histological and electrophysiological studies and fMRI spatial independent component analysis (sICA) and reports new findings by applying sICA to two existing datasets. The extant and new findings consistently demonstrate several novel features of brain functional organization not revealed by GLM. They include overlap of large-scale functional networks (FNs) and their concurrent opposite modulations, and no significant modulations in activity of most FNs across the whole brain during any task conditions. These novel features of brain functional organization are highly consistent with the brain's properties of functional heterogeneity, balanced E/I, and sparseness of neuronal activity, and may help reconcile inconsistent GLM findings.

Convergent evolution of complex brains and high intelligence

Within the animal kingdom, complex brains and high intelligence have evolved several to many times independently, e.g. among ecdysozoans in some groups of insects (e.g. blattoid, dipteran, hymenopteran taxa), among lophotrochozoans in octopodid molluscs, among vertebrates in teleosts (e.g. cichlids), corvid and psittacid birds, and cetaceans, elephants and primates. High levels of intelligence are invariantly bound to multimodal centres such as the mushroom bodies in insects, the vertical lobe in octopodids, the pallium in birds and the cerebral cortex in primates, all of which contain highly ordered associative neuronal networks. The driving forces for high intelligence may vary among the mentioned taxa, e.g. needs for spatial learning and foraging strategies in insects and cephalopods, for social learning in cichlids, instrumental learning and spatial orientation in birds and social as well as instrumental learning in primates.

Molecular evolution of WDR62, a gene that regulates neocorticogenesis

Human brain evolution is characterized by dramatic expansion in cerebral cortex size. WDR62 (WD repeat domain 62) is one of the important gene in controlling human cortical development. Mutations in WDR62 lead to primary microcephaly, a neurodevelopmental disease characterized by three to four fold reduction in cerebral cortex size of affected individuals. This study analyzes comparative protein evolutionary rate to provide a useful insight into the molecular evolution of WDR62 and hence pinpointed human specific amino acid replacements. Comparative analysis of human WDR62 with two archaic humans (Neanderthals and Denisovans) and modern human populations revealed that five hominin specific amino acid residues (human specific amino acids shared with two archaic humans) might have been accumulated in the common ancestor of extinct archaic humans and modern humans about 550,000–765,000 years ago. Collectively, the data demonstrates an acceleration of WDR62 sequence evolution in hominin lineage and suggests that the ability of WDR62 protein to mediate the neurogenesis has been altered in the course of hominin evolution.

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We trace the evolutionary history of WDR62 and its putative paralogs.

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We identify accelerated sequence evolution in human WDR62.

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We pinpoint eight human specific amino acid sites that reside on the C-terminal.

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Out of eight, six sites are shared with archaic humans.

Through the Immune Looking Glass: A Model for Brain Memory Strategies

The immune system (IS) and the central nervous system (CNS) are complex cognitive networks involved in defining the identity (self) of the individual through recognition and memory processes that enable one to anticipate responses to stimuli. Brain memory has traditionally been classified as either implicit or explicit on psychological and anatomical grounds, with reminiscences of the evolutionarily-based innate-adaptive IS responses. Beyond the multineuronal networks of the CNS, we propose a theoretical model of brain memory integrating the CNS as a whole. This is achieved by analogical reasoning between the operational rules of recognition and memory processes in both systems, coupled to an evolutionary analysis. In this new model, the hippocampus is no longer specifically ascribed to explicit memory but rather it both becomes part of the innate (implicit) memory system and tightly controls the explicit memory system. Alike the antigen presenting cells for the IS, the hippocampus would integrate transient and pseudo-specific (i.e., danger-fear) memories and would drive the formation of long-term and highly specific or explicit memories (i.e., the taste of the Proust's madeleine cake) by the more complex and recent, evolutionarily speaking, neocortex. Experimental and clinical evidence is provided to support the model. We believe that the singularity of this model's approximation could help to gain a better understanding of the mechanisms operating in brain memory strategies from a large-scale network perspective.

Principles of Intelligence: On Evolutionary Logic of the Brain

Humans and animals may encounter numerous events, objects, scenes, foods and countless social interactions in a lifetime. This means that the brain is constructed by evolution to deal with uncertainties and various possibilities. What is the architectural abstraction of intelligence that enables the brain to discover various possible patterns and knowledge about complex, evolving worlds? Here, I discuss the Theory of Connectivity–a “power-of-two” based, operational principle that can serve as a unified wiring and computational logic for organizing and constructing cell assemblies into the microcircuit-level building block, termed as functional connectivity motif (FCM). Defined by the power-of-two based equation, N = 2ⁱ−1, each FCM consists of the principal projection neuron cliques (N), ranging from those specific cliques receiving specific information inputs (i) to those general and sub-general cliques receiving various combinatorial convergent inputs. As the evolutionarily conserved logic, its validation requires experimental demonstrations of the following three major properties: (1) Anatomical prevalence—FCMs are prevalent across neural circuits, regardless of gross anatomical shapes; (2) Species conservancy—FCMs are conserved across different animal species; and (3) Cognitive universality—FCMs serve as a universal computational logic at the cell assembly level for processing a variety of cognitive experiences and flexible behaviors. More importantly, this Theory of Connectivity further predicts that the specific-to-general combinatorial connectivity pattern within FCMs should be preconfigured by evolution, and emerge innately from development as the brain’s computational primitives. This proposed design-principle can also explain the general purpose of the layered cortex and serves as its core computational algorithm.

Implications of cortical balanced excitation and inhibition, functional heterogeneity, and sparseness of neuronal activity in fMRI

Blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies often report inconsistent findings, probably due to brain properties such as balanced excitation and inhibition and functional heterogeneity. These properties indicate that different neurons in the same voxels may show variable activities including concurrent activation and deactivation, that the relationships between BOLD signal and neural activity (i.e., neurovascular coupling) are complex, and that increased BOLD signal may reflect reduced deactivation, increased activation, or both. The traditional general-linear-model-based-analysis (GLM-BA) is a univariate approach, cannot separate different components of BOLD signal mixtures from the same voxels, and may contribute to inconsistent findings of fMRI. Spatial independent component analysis (sICA) is a multivariate approach, can separate the BOLD signal mixture from each voxel into different source signals and measure each separately, and thus may reconcile previous conflicting findings generated by GLM-BA. We propose that methods capable of separating mixed signals such as sICA should be regularly used for more accurately and completely extracting information embedded in fMRI datasets.

Functional network overlap as revealed by fMRI using sICA and its potential relationships with functional heterogeneity, balanced excitation and inhibition, and sparseness of neuron activity

Functional magnetic resonance imaging (fMRI) studies traditionally use general linear model-based analysis (GLM-BA) and regularly report task-related activation, deactivation, or no change in activation in separate brain regions. However, several recent fMRI studies using spatial independent component analysis (sICA) find extensive overlap of functional networks (FNs), each exhibiting different task-related modulation (e.g., activation vs. deactivation), different from the dominant findings of GLM-BA. This study used sICA to assess overlap of FNs extracted from four datasets, each related to a different cognitive task. FNs extracted from each dataset overlapped with each other extensively across most or all brain regions and showed task-related concurrent increases, decreases, or no changes in activity. These findings indicate that neural substrates showing task-related concurrent but different modulations in activity intermix with each other and distribute across most of the brain. Furthermore, spatial correlation analyses found that most FNs were highly consistent in spatial patterns across different datasets. This finding indicates that these FNs probably reflect large-scale patterns of task-related brain activity. We hypothesize that FN overlaps as revealed by sICA might relate to functional heterogeneity, balanced excitation and inhibition, and population sparseness of neuron activity, three fundamental properties of the brain. These possibilities deserve further investigation.

Mechanical failure modes of chronically implanted planar silicon-based neural probes for laminar recording

Penetrating intracortical electrode arrays that record brain activity longitudinally are powerful tools for basic neuroscience research and emerging clinical applications. However, regardless of the technology used, signals recorded by these electrodes degrade over time. The failure mechanisms of these electrodes are understood to be a complex combination of the biological reactive tissue response and material failure of the device over time. While mechanical mismatch between the brain tissue and implanted neural electrodes have been studied as a source of chronic inflammation and performance degradation, the electrode failure caused by mechanical mismatch between different material properties and different structural components within a device have remained poorly characterized. Using Finite Element Model (FEM) we simulate the mechanical strain on a planar silicon electrode. The results presented here demonstrate that mechanical mismatch between iridium and silicon leads to concentrated strain along the border of the two materials. This strain is further focused on small protrusions such as the electrical traces in planar silicon electrodes. These findings are confirmed with chronic in vivo data (133-189 days) in mice by correlating a combination of single-unit electrophysiology, evoked multi-unit recordings, electrochemical impedance spectroscopy, and scanning electron microscopy from traces and electrode sites with our modeling data. Several modes of mechanical failure of chronically implanted planar silicon electrodes are found that result in degradation and/or loss of recording. These findings highlight the importance of strains and material properties of various subcomponents within an electrode array.

Effect of temperature and glia in brain size enlargement and origin of allometric body-brain size scaling in vertebrates

Background

Brain signaling requires energy. The cost of maintaining and supporting energetically demanding neurons is the key constraint on brain size. The dramatic increase in brain size among mammals and birds cannot be understood without solving this conundrum: larger brains, with more neurons, consume more energy.

Results

Here we examined the intrinsic relationships between metabolism, body-brain size ratios and neuronal densities of both endothermic and ectothermic animals. We formulated a general model to elucidate the key factors that correlate with brain enlargement, and the origin of allometric body-brain size scaling. This framework identified temperature as a critical factor in brain enlargement via temperature-regulated changes in metabolism. Our framework predicts that ectothermic animals living in tropical climates should have brain sizes that are several times larger than those of ectothermic animals living in cold climates. This prediction was confirmed by data from experiments in fish brains. Our framework also suggests that a rapid increase in the number of less energy-demanding glial cells may be another important factor contributing to the ten-fold increase in the brain sizes of endotherms compared with ectotherms.

Conclusions

This study thus provides a quantitative theory that predicts the brain sizes of all the major types of animals and quantifies the contributions of temperature-dependent metabolism, body size and neuronal density.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-014-0178-z) contains supplementary material, which is available to authorized users.

Evolution of the human brain: when bigger is better

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 object of this review is to present current perspectives on primate brain evolution, especially in humans, and to examine some hypothetical organizing principles that underlie the brain's complex organization. Some of the design principles and operational modes that underlie the information processing capacity of the cerebral cortex in primates will be explored. It is shown that the development of the cortex coordinates folding with connectivity in a way that produces smaller and faster brains, then otherwise would have been possible. In view of the central importance placed on brain evolution in explaining the success of our own species, one may wonder whether there are physical limits that constrain its processing power and evolutionary potential. It will be argued that at a brain size of about 3500 cm(3), corresponding to a brain volume two to three times that of modern man, the brain seems to reach its maximum processing capacity. The larger the brain grows beyond this critical size, the less efficient it will become, thus limiting any improvement in cognitive power.

Human brain evolution: transcripts, metabolites and their regulators

What evolutionary events led to the emergence of human cognition? Although the genetic differences separating modern humans from both non-human primates (for example, chimpanzees) and archaic hominins (Neanderthals and Denisovans) are known, linking human-specific mutations to the cognitive phenotype remains a challenge. One strategy is to focus on human-specific changes at the level of intermediate phenotypes, such as gene expression and metabolism, in conjunction with evolutionary changes in gene regulation involving transcription factors, microRNA and proximal regulatory elements. In this Review we show how this strategy has yielded some of the first hints about the mechanisms of human cognition.