Jean-Pierre Changeux’s research while affiliated with University of California, San Diego and other places

In this interview, Guillaume Dumas reaches out to Jean-Pierre Changeux to offer a wide-ranging view on consciousness, spanning over its fundamental molecular mechanisms up to its social dimension. They further discuss the exploration of altered states of consciousness and its relation to artistic practice. They finally tackle the opportunities of some of the prominent fields of future research such as artificial intelligence and highlight the importance of multidisciplinary research in advancing the study of consciousness.

The Evolutionary Roots of Human Brain Diseases takes an innovative approach and assembles recent findings ranging from evolutionary biology and anthropology to clinical neurosciences, all showing the price on health of human brain evolution. Written by experts in their field, the chapters explore the tenet that extensive human brain development during evolution has given rise to exclusively human brain diseases, both priming and impacting their clinical expression. There are presentations on cerebral cellular specificities or human-specific network developments, detailed discussions of neurological or psychiatric diseases with an evolutionary focus, and chapters exploring evolutionarily grounded medication developments as well as cultural and societal repercussions. Evolutionary concepts ranging from genetic pleiotropic antagonism to disease remnants of ancient behaviors crucial for survival are presented. The horizon is extended to include potential repercussions of ongoing human evolution on the human brain when cultural evolution outpaces biological evolution.

Working with François Gros was a privileged moment in my scientific life, enabling me to appreciate a scientific personality whose generosity knew no bounds and whose vision of science was far ahead of its time.

Brain research has in recent years indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modeling at multiple scales – from molecules to the whole system. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain integrates high-quality basic research, systematic data integration across multiple scales, a new culture of large-scale collaboration and translation into applications. A systematic approach, as pioneered in Europe’s Human Brain Project (HBP), will be essential in meeting the pressing medical and technological challenges of the coming decade. The aims of this paper are To develop a concept for the coming decade of digital brain research To discuss it with the research community at large, with the aim of identifying points of convergence and common goals To provide a scientific framework for current and future development of EBRAINS To inform and engage stakeholders, funding organizations and research institutions regarding future digital brain research To identify and address key ethical and societal issues While we do not claim that there is a ‘one size fits all’ approach to addressing these aspects, we are convinced that discussions around the theme of digital brain research will help drive progress in the broader field of neuroscience.

Recent advances in neurobiology, paleontology, and paleogenetics allow us to associate changes in brain size and organization with three main “moments” of increased behavioral complexity and, more speculatively, language development. First, Australopiths display a significant increase in brain size relative to the great apes and an incipient extension of postnatal brain development. However, their cortical organization remains essentially similar to that of apes. Second, over the last 2 My, with two notable exceptions, brain size increases dramatically, partly in relation to changes in body size. Differential enlargements and reorganizations of cortical areas lay the foundation for the “language-ready” brain and cumulative culture of later Homo species. Third, in Homo sapiens, brain size remains fairly stable over the last 300,000 years but an important cerebral reorganization takes place. It affects the frontal and temporal lobes, the parietal areas and the cerebellum and resulted in a more globular shape of the brain. These changes are associated, among others, with an increased development of long-distance—horizontal—connections. A few regulatory genetic events took place in the course of this hominization process with, in particular, enhanced neuronal proliferation and global brain connectivity.

What structural and connectivity features of the human brain help to explain the extraordinary human cognitive abilities? We recently proposed a set of relevant connectomic fundamentals, some of which arise from the size scaling of the human brain relative to other primate brains, while others of these fundamentals may be uniquely human. In particular, we suggested that the remarkable increase of the size of the human brain due to its prolonged prenatal development has brought with it an increased sparsification, hierarchical modularization, as well as increased depth and cytoarchitectonic differentiation of brain networks. These characteristic features are complemented by a shift of projection origins to the upper layers of many cortical areas as well as the significantly prolonged postnatal development and plasticity of the upper cortical layers. Another fundamental aspect of cortical organization that has emerged in recent research is the alignment of diverse features of evolution, development, cytoarchitectonics, function, and plasticity along a principal, natural cortical axis from sensory (“outside”) to association (“inside”) areas. Here we highlight how this natural axis is integrated in the characteristic organization of the human brain. In particular, the human brain displays a developmental expansion of outside areas and a stretching of the natural axis such that outside areas are more widely separated from each other and from inside areas than in other species. We outline some functional implications of this characteristic arrangement.

Several neuronal mechanisms have been proposed to account for the formation of cognitive abilities through postnatal interactions with the physical and sociocultural environment. Here, we introduce a three-level computational model of information processing and acquisition of cognitive abilities. We propose minimal architectural requirements to build these levels, and how the parameters affect their performance and relationships. The first sensorimotor level handles local nonconscious processing, here during a visual classification task. The second level or cognitive level globally integrates the information from multiple local processors via long-ranged connections and synthesizes it in a global, but still nonconscious, manner. The third and cognitively highest level handles the information globally and consciously. It is based on the global neuronal workspace (GNW) theory and is referred to as the conscious level. We use the trace and delay conditioning tasks to, respectively, challenge the second and third levels. Results first highlight the necessity of epigenesis through the selection and stabilization of synapses at both local and global scales to allow the network to solve the first two tasks. At the global scale, dopamine appears necessary to properly provide credit assignment despite the temporal delay between perception and reward. At the third level, the presence of interneurons becomes necessary to maintain a self-sustained representation within the GNW in the absence of sensory input. Finally, while balanced spontaneous intrinsic activity facilitates epigenesis at both local and global scales, the balanced excitatory/inhibitory ratio increases performance. We discuss the plausibility of the model in both neurodevelopmental and artificial intelligence terms.

Two forms of associative learning—delay conditioning and trace conditioning—have been widely investigated in humans and higher-order mammals¹. In delay conditioning, an unconditioned stimulus (for example, an electric shock) is introduced in the final moments of a conditioned stimulus (for example, a tone), with both ending at the same time. In trace conditioning, a ‘trace’ interval separates the conditioned stimulus and the unconditioned stimulus. Trace conditioning therefore relies on maintaining a neural representation of the conditioned stimulus after its termination (hence making distraction possible²), to learn the conditioned stimulus–unconditioned stimulus contingency³; this makes it more cognitively demanding than delay conditioning⁴. Here, by combining virtual-reality behaviour with neurogenetic manipulations and in vivo two-photon brain imaging, we show that visual trace conditioning and delay conditioning in Drosophila mobilize R2 and R4m ring neurons in the ellipsoid body. In trace conditioning, calcium transients during the trace interval show increased oscillations and slower declines over repeated training, and both of these effects are sensitive to distractions. Dopaminergic activity accompanies signal persistence in ring neurons, and this is decreased by distractions solely during trace conditioning. Finally, dopamine D1-like and D2-like receptor signalling in ring neurons have different roles in delay and trace conditioning; dopamine D1-like receptor 1 mediates both forms of conditioning, whereas the dopamine D2-like receptor is involved exclusively in sustaining ring neuron activity during the trace interval of trace conditioning. These observations are similar to those previously reported in mammals during arousal⁵, prefrontal activation⁶ and high-level cognitive learning7,8.

Several neuronal mechanisms have been proposed to account for the formation of cognitive abilities through postnatal interactions with the physical and socio-cultural environment. Here, we introduce a three-level computational model of information processing and acquisition of cognitive abilities. We propose minimal architectural requirements to build these levels and how the parameters affect their performance and relationships. The first sensorimotor level handles local nonconscious processing, here during a visual classification task. The second level or cognitive level globally integrates the information from multiple local processors via long-ranged connections and synthesizes it in a global, but still nonconscious manner. The third and cognitively highest level handles the information globally and consciously. It is based on the Global Neuronal Workspace (GNW) theory and is referred to as conscious level. We use trace and delay conditioning tasks to, respectively, challenge the second and third levels. Results first highlight the necessity of epigenesis through selection and stabilization of synapses at both local and global scales to allow the network to solve the first two tasks. At the global scale, dopamine appears necessary to properly provide credit assignment despite the temporal delay between perception and reward. At the third level, the presence of interneurons becomes necessary to maintain a self-sustained representation within the GNW in the absence of sensory input. Finally, while balanced spontaneous intrinsic activity facilitates epigenesis at both local and global scales, the balanced excitatory-inhibitory ratio increases performance. Finally, we discuss the plausibility of the model in both neurodevelopmental and artificial intelligence terms.