Neuronal models of cognitive functions

From animal models to human individuality: Integrative approaches to the study of brain plasticity

Plasticity allows organisms to form lasting adaptive changes in neural structures in response to interactions with the environment. It serves both species-general functions and individualized skill acquisition. To better understand human plasticity, we need to strengthen the dialogue between human research and animal models. Therefore, we propose to (1) enhance the interpretability of macroscopic methods used in human research by complementing molecular and fine-structural measures used in animals with such macroscopic methods, preferably applied to the same animals, to create macroscopic metrics common to both examined species; (2) launch dedicated cross-species research programs, using either well-controlled experimental paradigms, such as motor skill acquisition, or more naturalistic environments, where individuals of either species are observed in their habitats; and (3) develop conceptual and computational models linking molecular and fine-structural events to phenomena accessible by macroscopic methods. In concert, these three component strategies can foster new insights into the nature of plastic change.

Sources of richness and ineffability for phenomenally conscious states

Conscious states-state that there is something it is like to be in-seem both rich or full of detail and ineffable or hard to fully describe or recall. The problem of ineffability, in particular, is a longstanding issue in philosophy that partly motivates the explanatory gap: the belief that consciousness cannot be reduced to underlying physical processes. Here, we provide an information theoretic dynamical systems perspective on the richness and ineffability of consciousness. In our framework, the richness of conscious experience corresponds to the amount of information in a conscious state and ineffability corresponds to the amount of information lost at different stages of processing. We describe how attractor dynamics in working memory would induce impoverished recollections of our original experiences, how the discrete symbolic nature of language is insufficient for describing the rich and high-dimensional structure of experiences, and how similarity in the cognitive function of two individuals relates to improved communicability of their experiences to each other. While our model may not settle all questions relating to the explanatory gap, it makes progress toward a fully physicalist explanation of the richness and ineffability of conscious experience-two important aspects that seem to be part of what makes qualitative character so puzzling.

Continuity and change in neural plasticity through embryonic morphogenesis, fetal activity-dependent synaptogenesis, and infant memory consolidation

There is an apparent continuity in human neural development that can be traced to venerable themes of vertebrate morphogenesis that have shaped the evolution of the reptilian telencephalon (including both primitive three-layered cortex and basal ganglia) and then the subsequent evolution of the mammalian six-layered neocortex. In this theoretical analysis, we propose that an evolutionary-developmental analysis of these general morphogenetic themes can help to explain the embryonic development of the dual divisions of the limbic system that control the dorsal and ventral networks of the human neocortex. These include the archicortical (dorsal limbic) Papez circuits regulated by the hippocampus that organize spatial, contextual memory, as well as the paleocortical (ventral limbic) circuits that organize object memory. We review evidence that these dorsal and ventral limbic divisions are controlled by the differential actions of brainstem lemnothalamic and midbrain collothalamic arousal control systems, respectively, thereby traversing the vertebrate subcortical neuraxis. These dual control systems are first seen shaping the phyletic morphogenesis of the archicortical and paleocortical foundations of the forebrain in embryogenesis. They then provide dual modes of activity-dependent synaptic organization in the active (lemnothalamic) and quiet (collothalamic) stages of fetal sleep. Finally, these regulatory systems mature to form the major systems of memory consolidation of postnatal development, including the rapid eye movement (lemnothalamic) consolidation of implicit memory and social attachment in the first year, and then-in a subsequent stage-the non-REM (collothalamic) consolidation of explicit memory that is integral to the autonomy and individuation of the second year of life.

Synchronization in simplicial complexes of memristive Rulkov neurons

Simplicial complexes are mathematical constructions that describe higher-order interactions within the interconnecting elements of a network. Such higher-order interactions become increasingly significant in neuronal networks since biological backgrounds and previous outcomes back them. In light of this, the current research explores a higher-order network of the memristive Rulkov model. To that end, the master stability functions are used to evaluate the synchronization of a network with pure pairwise hybrid (electrical and chemical) synapses alongside a network with two-node electrical and multi-node chemical connections. The findings provide good insight into the impact of incorporating higher-order interaction in a network. Compared to two-node chemical synapses, higher-order interactions adjust the synchronization patterns to lower multi-node chemical coupling parameter values. Furthermore, the effect of altering higher-order coupling parameter value on the dynamics of neurons in the synchronization state is researched. It is also shown how increasing network size can enhance synchronization by lowering the value of coupling parameters whereby synchronization occurs. Except for complete synchronization, cluster synchronization is detected for higher electrical coupling strength values wherein the neurons are out of the completed synchronization state.

What triggers explicit awareness in implicit sequence learning? Implications from theories of consciousness

This article aims to continue the debate on how explicit, conscious knowledge can arise in an implicit learning situation. We review hitherto existing theoretical views and evaluate their compatibility with two current, successful scientific concepts of consciousness: The Global Workspace Theory and Higher-Order Thought Theories. In this context, we introduce the Unexpected Event Hypothesis (Frensch et al., Attention and implicit learning, John Benjamins Publishing Company, 2003) in an elaborated form and discuss its advantage in explaining the emergence of conscious knowledge in an implicit learning situation.

What Cognitive Mechanism, When, Where, and Why? Exploring the Decision Making of University and Professional Rugby Union Players During Competitive Matches

Over the past 50 years decision making research in team invasion sport has been dominated by three research perspectives, information processing, ecological dynamics, and naturalistic decision making. Recently, attempts have been made to integrate perspectives, as conceptual similarities demonstrate the decision making process as an interaction between a players perception of game information and the individual and collective capability to act on it. Despite this, no common ground has been found regarding what connects perception and action during performance. The differences between perspectives rest on the role of stored mental representations, that may, or may not facilitate the retrieval of appropriate responses in time pressured competitive environments. Additionally, in team invasion sports like rugby union, the time available to players to perceive, access memory and act, alters rapidly between specific game situations. Therefore, the aim of this study was to examine theoretical differences and the mechanisms that underpin them, through the vehicle of rugby union. Sixteen semi-elite rugby union players took part in two post-game procedures to explore the following research objectives; (i) to consider how game situations influence players perception of information; (ii) to consider how game situations influence the application of cognitive mechanisms whilst making decisions; and (iii) to identify the influence of tactics and/or strategy on player decision making. Deductive content analysis and elementary units of meaning derived from self-confrontation elicitation interviews indicate that specific game situations such as; the lineout, scrum or open phases of play or the tackle situation in attack or defence all provide players with varying complexity of perceptual information, formed through game information and time available to make decisions. As time increased, players were more likely to engage with task-specific declarative knowledge-of the game, stored as mental representations. As time diminished, players tended to diagnose and update their knowledge-in the game in a rapid fashion. Occasionally, when players described having no time, they verbalised reacting on instinct through a direct connection between perception and action. From these findings, clear practical implications and directions for future research and dissemination are discussed.

Observing Plasticity of the Auditory System: Volumetric Decreases Along with Increased Functional Connectivity in Aspiring Professional Musicians

Playing music relies on several sensory systems and the motor system, and poses strong demands on control processes, hence, offering an excellent model to study how experience can mold brain structure and function. Although most studies on neural correlates of music expertise rely on cross-sectional comparisons, here we compared within-person changes over time in aspiring professionals intensely preparing for an entrance exam at a University of the Arts to skilled amateur musicians not preparing for a music exam. In the group of aspiring professionals, we observed gray-matter volume decrements in left planum polare, posterior insula, and left inferior frontal orbital gyrus over a period of about 6 months that were absent among the amateur musicians. At the same time, the left planum polare, the largest cluster of structural change, showed increasing functional connectivity with left and right auditory cortex, left precentral gyrus, left supplementary motor cortex, left and right postcentral gyrus, and left cingulate cortex, all regions previously identified to relate to music expertise. In line with the expansion-renormalization pattern of brain plasticity (Wenger et al., 2017a. Expansion and renormalization of human brain structure during skill acquisition. Trends Cogn Sci. 21:930-939.), the aspiring professionals might have been in the selection and refinement period of plastic change.

A Review and Hypothesized Model of the Mechanisms That Underpin the Relationship Between Inflammation and Cognition in the Elderly

Age is associated with increased risk for several disorders including dementias, cardiovascular disease, atherosclerosis, obesity, and diabetes. Age is also associated with cognitive decline particularly in cognitive domains associated with memory and processing speed. With increasing life expectancies in many countries, the number of people experiencing age-associated cognitive impairment is increasing and therefore from both economic and social terms the amelioration or slowing of cognitive aging is an important target for future research. However, the biological causes of age associated cognitive decline are not yet, well understood. In the current review, we outline the role of inflammation in cognitive aging and describe the role of several inflammatory processes, including inflamm-aging, vascular inflammation, and neuroinflammation which have both direct effect on brain function and indirect effects on brain function via changes in cardiovascular function.

Expansion and Renormalization of Human Brain Structure During Skill Acquisition

Research on human brain changes during skill acquisition has revealed brain volume expansion in task-relevant areas. However, the large number of skills that humans acquire during ontogeny militates against plasticity as a perpetual process of volume growth. Building on animal models and available theories, we promote the expansion-renormalization model for plastic changes in humans. The model predicts an initial increase of gray matter structure, potentially reflecting growth of neural resources like neurons, synapses, and glial cells, which is followed by a selection process operating on this new tissue leading to a complete or partial return to baseline of the overall volume after selection has ended. The model sheds new light on available evidence and current debates and fosters the search for mechanistic explanations.

Development of the macaque face-patch system

Face recognition is highly proficient in humans and other social primates; it emerges in infancy, but the development of the neural mechanisms supporting this behaviour is largely unknown. We use blood-volume functional MRI to monitor longitudinally the responsiveness to faces, scrambled faces, and objects in macaque inferotemporal cortex (IT) from 1 month to 2 years of age. During this time selective responsiveness to monkey faces emerges. Some functional organization is present at 1 month; face-selective patches emerge over the first year of development, and are remarkably stable once they emerge. Face selectivity is refined by a decreasing responsiveness to non-face stimuli.

Project Management between Will and Representation

This article challenges some deep-rooted assumptions of project management. Inspired by the work of the German philosopher, Arthur Schopenhauer, it calls for looking at projects through two complementary lenses: one that accounts for cognitive and representational aspects and one that accounts for material and volitional aspects. Understanding the many ways in which these aspects transpire and interact in projects sheds new light on project organizations, as imperfect and fragile representations that chase a shifting nexus of intractable human, social, technical, and material processes. This, in turn, can bring about a new grasp of notions such as value, knowledge, complexity, and risk.

The Role of Dendritic Signaling in the Anesthetic Suppression of Consciousness

Despite considerable progress in the identification of the molecular targets of general anesthetics, it remains unclear how these drugs affect the brain at the systems level to suppress consciousness. According to recent proposals, anesthetics may achieve this feat by interfering with corticocortical top–down processes, that is, by interrupting information flow from association to early sensory cortices. Such a view entails two immediate questions. First, at which anatomical site, and by virtue of which physiological mechanism, do anesthetics interfere with top–down signals? Second, why does a breakdown of top–down signaling cause unconsciousness? While an answer to the first question can be gleaned from emerging neurophysiological evidence on dendritic signaling in cortical pyramidal neurons, a response to the second is offered by increasingly popular theoretical frameworks that place the element of prediction at the heart of conscious perception.

The emergence of consciousness: Science and ethics

The newborn human infant is conscious at a minimal level. It is aware of its body, itself and to some extent of the outside world. It recognizes faces and vowels to which it has been exposed. It expresses emotions like joy. Functional magnetic resonance imaging of the newborn brain shows highest activity in the somatosensory, auditory, and visual cortex but less activity in association area and the prefrontal cortex as compared with adults. There is an incomplete default mode network which is assumed to be related to consciousness. Although the fetus reacts to pain, maternal speaking, etc., it is probably not aware of this due to the low oxygen level and sedation. Assuming that consciousness is mainly localized in the cortex, consciousness cannot emerge before 24 gestational weeks when the thalamocortical connections from the sense organs are established. Thus the limit of legal abortion at 22-24 weeks in many countries makes sense. It should also be possible to withdraw or withhold life-saving therapy of extremely preterm infants, especially if they are severely brain-damaged. This may also apply to full-term infants with grade III hypoxic-ischemic encephalopathy, who show no signs of consciousness.

Structural brain plasticity in adult learning and development

Recent research using magnetic resonance imaging has documented changes in the adult human brain's grey matter structure induced by alterations in experiential demands. We review this research and relate it to models of brain plasticity from related strands of research, such as work on animal models. This allows us to generate recommendations and predictions for future research that may advance the understanding of the function, sequential progression, and microstructural nature of experience-dependent changes in regional brain volumes. Informed by recent evidence on adult age differences in structural brain plasticity, we show how understanding learning-related changes in human brain structure can expand our knowledge about adult development and aging. We hope that this review will promote research on the mechanisms regulating experience-dependent structural plasticity of the adult human brain.

Contributions of Dynamic Systems Theory to Cognitive Development

This paper examines the contributions of dynamic systems theory to the field of cognitive development, focusing on modeling using dynamic neural fields. A brief overview highlights the contributions of dynamic systems theory and the central concepts of dynamic field theory (DFT). We then probe empirical predictions and findings generated by DFT around two examples-the DFT of infant perseverative reaching that explains the Piagetian A-not-B error, and the DFT of spatial memory that explain changes in spatial cognition in early development. A systematic review of the literature around these examples reveals that computational modeling is having an impact on empirical research in cognitive development; however, this impact does not extend to neural and clinical research. Moreover, there is a tendency for researchers to interpret models narrowly, anchoring them to specific tasks. We conclude on an optimistic note, encouraging both theoreticians and experimentalists to work toward a more theory-driven future.

Cannabinoid mitigation of neuronal morphological change important to development and learning: insight from a zebra finch model of psychopharmacology

Normal CNS development proceeds through late-postnatal stages of adolescent development. The activity-dependence of this development underscores the significance of CNS-active drug exposure prior to completion of brain maturation. Exogenous modulation of signaling important in regulating normal development is of particular concern. This mini-review presents a summary of the accumulated behavioral, physiological and biochemical evidence supporting such a key regulatory role for endocannabinoid signaling during late-postnatal CNS development. Our focus is on the data obtained using a unique zebra finch model of developmental psychopharmacology. This animal has allowed investigation of neuronal morphological effects essential to establishment and maintenance of neural circuitry, including processes related to synaptogenesis and dendritic spine dynamics. Altered neurophysiology that follows exogenous cannabinoid exposure during adolescent development has the potential to persistently alter cognition, learning and memory.

Progressive and regressive developmental changes in neural substrates for face processing: testing specific predictions of the Interactive Specialization account

Face processing undergoes a fairly protracted developmental time course but the neural underpinnings are not well understood. Prior fMRI studies have only examined progressive changes (i.e., increases in specialization in certain regions with age), which would be predicted by both the Interactive Specialization (IS) and maturational theories of neural development. To differentiate between these accounts, the present study also examined regressive changes (i.e., decreases in specialization in certain regions with age), which is predicted by the IS but not maturational account. The fMRI results show that both progressive and regressive changes occur, consistent with IS. Progressive changes mostly occurred in occipital-fusiform and inferior frontal cortex whereas regressive changes largely emerged in parietal and lateral temporal cortices. Moreover, inconsistent with the maturational account, all of the regions involved in face viewing in adults were active in children, with some regions already specialized for face processing by 5 years of age and other regions activated in children but not specifically for faces. Thus, neurodevelopment of face processing involves dynamic interactions among brain regions including age-related increases and decreases in specialization and the involvement of different regions at different ages. These results are more consistent with IS than maturational models of neural development.

Levels of analysis: philosophical issues

A focal concern in the philosophy of cognitive science is whether the world is fundamentally organized into hierarchies of levels and whether mental phenomena exemplify such higher-level regularities and hence are unexplainable by lower-level theory. Levels of analysis represent different stances from which predictive and explanatory theories are constructed, and each level of analysis contains a set of kind terms representing things in nature, predicates representing properties or relations, and law-like generalizations or principles. The concept of levels of analysis, which plays a central role in debates over the cognitive architecture of the mind in cognitive science, is concerned mainly with the choice of which level of analysis can be expected to maximize the predictability and explanatory power of cognitive modeling. The core philosophical issues concerning the levels of analysis are the problem of theoretical reduction between the levels, the concept of supervenience, the problem of emergent properties, and the conceptual coherence of the notion of downward causation. WIREs Cogn Sci 2012, 3:315-325. doi: 10.1002/wcs.1179 For further resources related to this article, please visit the WIREs website.

Selectionist and evolutionary approaches to brain function: a critical appraisal

We consider approaches to brain dynamics and function that have been claimed to be Darwinian. These include Edelman’s theory of neuronal group selection, Changeux’s theory of synaptic selection and selective stabilization of pre-representations, Seung’s Darwinian synapse, Loewenstein’s synaptic melioration, Adam’s selfish synapse, and Calvin’s replicating activity patterns. Except for the last two, the proposed mechanisms are selectionist but not truly Darwinian, because no replicators with information transfer to copies and hereditary variation can be identified in them. All of them fit, however, a generalized selectionist framework conforming to the picture of Price’s covariance formulation, which deliberately was not specific even to selection in biology, and therefore does not imply an algorithmic picture of biological evolution. Bayesian models and reinforcement learning are formally in agreement with selection dynamics. A classification of search algorithms is shown to include Darwinian replicators (evolutionary units with multiplication, heredity, and variability) as the most powerful mechanism for search in a sparsely occupied search space. Examples are given of cases where parallel competitive search with information transfer among the units is more efficient than search without information transfer between units. Finally, we review our recent attempts to construct and analyze simple models of true Darwinian evolutionary units in the brain in terms of connectivity and activity copying of neuronal groups. Although none of the proposed neuronal replicators include miraculous mechanisms, their identification remains a challenge but also a great promise.

Late-postnatal cannabinoid exposure persistently elevates dendritic spine densities in area X and HVC song regions of zebra finch telencephalon

Centrally acting cannabinoids are well known for their ability to impair functions associated with both learning and memory but appreciation of the physiological mechanisms underlying these actions, particularly those that persist, remains incomplete. Our earlier studies have shown that song stereotypy is persistently reduced in male zebra finches that have been developmentally exposed to cannabinoids. In the present work, we examined the extent to which changes in neuronal morphology (dendritic spine densities and soma size) within brain regions associated with zebra finch vocal learning are affected by late-postnatal cannabinoid agonist exposure. We found that daily treatment with the cannabinoid agonist WIN55212-2 (WIN, 1mg/kg IM) is associated with 27% and 31% elevations in dendritic spine densities in the song regions Area X and HVC, respectively. We also found an overall increase in cell diameter within HVC. Changes in dendritic spine densities were only produced following developmental exposure; treatments given to adults that had completed vocal learning were not effective. These findings have important implications for understanding how repeated cannabinoid exposure can produce significant, lasting alteration of brain morphology, which may contribute to altered development and behavior.

Early bifrontal brain injury: disturbances in cognitive function development

We describe six psychomotor, language, and neuropsychological sequential developmental evaluations in a boy who sustained a severe bifrontal traumatic brain injury (TBI) at 19 months of age. Visuospatial, drawing, and writing skills failed to develop normally. Gradually increasing difficulties were noted in language leading to reading and spontaneous speech difficulties. The last two evaluations showed executive deficits in inhibition, flexibility, and working memory. Those executive abnormalities seemed to be involved in the other impairments. In conclusion, early frontal brain injury disorganizes the development of cognitive functions, and interactions exist between executive function and other cognitive functions during development.

The use of Artificial Neural Networks to classify primate vocalizations: A pilot study on black lemurs

The identification of the vocal repertoire of a species represents a crucial prerequisite for a correct interpretation of animal behavior. Artificial Neural Networks (ANNs) have been widely used in behavioral sciences, and today are considered a valuable classification tool for reducing the level of subjectivity and allowing replicable results across different studies. However, to date, no studies have applied this tool to nonhuman primate vocalizations. Here, we apply for the first time ANNs, to discriminate the vocal repertoire in a primate species, Eulemur macaco macaco. We designed an automatic procedure to extract both spectral and temporal features from signals, and performed a comparative analysis between a supervised Multilayer Perceptron and two statistical approaches commonly used in primatology (Discriminant Function Analysis and Cluster Analysis), in order to explore pros and cons of these methods in bioacoustic classification. Our results show that ANNs were able to recognize all seven vocal categories previously described (92.5-95.6%) and perform better than either statistical analysis (76.1-88.4%). The results show that ANNs can provide an effective and robust method for automatic classification also in primates, suggesting that neural models can represent a valuable tool to contribute to a better understanding of primate vocal communication. The use of neural networks to identify primate vocalizations and the further development of this approach in studying primate communication are discussed.

Cortical representations of symbols, objects, and faces are pruned back during early childhood

Regions of human ventral extrastriate visual cortex develop specializations for natural categories (e.g., faces) and cultural artifacts (e.g., words). In adults, category-based specializations manifest as greater neural responses in visual regions of the brain (e.g., fusiform gyrus) to some categories over others. However, few studies have examined how these specializations originate in the brains of children. Moreover, it is as yet unknown whether the development of visual specializations hinges on "increases" in the response to the preferred categories, "decreases" in the responses to nonpreferred categories, or "both." This question is relevant to a long-standing debate concerning whether neural development is driven by building up or pruning back representations. To explore these questions, we measured patterns of visual activity in 4-year-old children for 4 categories (faces, letters, numbers, and shoes) using functional magnetic resonance imaging. We report 2 key findings regarding the development of visual categories in the brain: 1) the categories "faces" and "symbols" doubly dissociate in the fusiform gyrus before children can read and 2) the development of category-specific responses in young children depends on cortical responses to nonpreferred categories that decrease as preferred category knowledge is acquired.

Development of global cortical networks in early infancy

Human cognition and behaviors are subserved by global networks of neural mechanisms. Although the organization of the brain is a subject of interest, the process of development of global cortical networks in early infancy has not yet been clarified. In the present study, we explored developmental changes in these networks from several days to 6 months after birth by examining spontaneous fluctuations in brain activity, using multichannel near-infrared spectroscopy. We set up 94 measurement channels over the frontal, temporal, parietal, and occipital regions of the infant brain. The obtained signals showed complex time-series properties, which were characterized as 1/f fluctuations. To reveal the functional connectivity of the cortical networks, we calculated the temporal correlations of continuous signals between all the pairs of measurement channels. We found that the cortical network organization showed regional dependency and dynamic changes in the course of development. In the temporal, parietal, and occipital regions, connectivity increased between homologous regions in the two hemispheres and within hemispheres; in the frontal regions, it decreased progressively. Frontoposterior connectivity changed to a "U-shaped" pattern within 6 months: it decreases from the neonatal period to the age of 3 months and increases from the age of 3 months to the age of 6 months. We applied cluster analyses to the correlation coefficients and showed that the bilateral organization of the networks begins to emerge during the first 3 months of life. Our findings suggest that these developing networks, which form multiple clusters, are precursors of the functional cerebral architecture.

Control of transient synchronization with external stimuli

A network of coupled chaotic oscillators can switch spontaneously to a state of collective synchronization at some critical coupling strength. We show that for a locally coupled network of units with coexisting quiescence and chaotic spiking states, set slightly below the critical coupling value, the collective excitable or bistable states of synchronization arise in response to a stimulus applied to a single node. We provide an explanation of this behavior and show that it is due to a combination of the dynamical properties of a single node and the coupling topology. By the use of entropy as a collective indicator, we present a new method for controlling the transient synchronization.

Development and self-regulatory structures of the mind

From their early roots in embryology, parallels are drawn between the major psychological and biological foci of organismic theories. Neural plasticity and concepts of causality in developmental systems are discussed. Because the nature of the developmental process necessitates addressing the nonlinear dynamics of complex systems, it is theorized that causal explanations in neural development, just as is the case with psychological processes, should emphasize the individual's active strivings for self-organization as the major determinant of ontogenesis. Whether or not they cohere to form an integrated self, it is hypothesized that the homeostatic, self-regulatory structures of the mind are the major stabilities in the chaotic dynamics of psychological and neural development.

Colloid-guided assembly of oriented 3D neuronal networks

A central challenge in neuroscience is to understand the formation and function of three-dimensional (3D) neuronal networks. In vitro studies have been mainly limited to measurements of small numbers of neurons connected in two dimensions. Here we demonstrate the use of colloids as moveable supports for neuronal growth, maturation, transfection and manipulation, where the colloids serve as guides for the assembly of controlled 3D, millimeter-sized neuronal networks. Process growth can be guided into layered connectivity with a density similar to what is found in vivo. The colloidal superstructures are optically transparent, enabling remote stimulation and recording of neuronal activity using layer-specific expression of light-activated channels and indicator dyes. The modular approach toward in vitro circuit construction provides a stepping stone for applications ranging from basic neuroscience to neuron-based screening of targeted drugs.

Brain dynamics across levels of organization

After initially presenting evidence that the electrical activity recorded from the brain surface can reflect metastable state transitions of neuronal configurations at the mesoscopic level, I will suggest that their patterns may correspond to the distinctive spatio-temporal activity in the dynamic core (DC) and the global neuronal workspace (GNW), respectively, in the models of the Edelman group on the one hand, and of Dehaene-Changeux, on the other. In both cases, the recursively reentrant activity flow in intra-cortical and cortical-subcortical neuron loops plays an essential and distinct role. Reasons will be given for viewing the temporal characteristics of this activity flow as signature of self-organized criticality (SOC), notably in reference to the dynamics of neuronal avalanches. This point of view enables the use of statistical physics approaches for exploring phase transitions, scaling and universality properties of DC and GNW, with relevance to the macroscopic electrical activity in EEG and EMG.

The autistic syndrome and endogenous ion cyclotron resonance: state of the art

The autistic syndrome is a multigenic disease whose expression is different according to the level of involvement of different structures in the central nervous system. The pathogenesis is unknown. No completely effective medical therapy has yet been demonstrated. Accepting the request of the families of eight autistic children in Lomazzo, Milan and Naples, we used ion cyclotron resonance (Seqex therapy) therapeutic support after many other therapies had been already carried out on these patients. After regimens consisting of 20-30 treatments with ICR, improvements were noted in all cases.

Excess of neurons in the human newborn mediodorsal thalamus compared with that of the adult

The aim of this study was to quantify the total number of neurons and glial cells in the mediodorsal nucleus of the thalamus (MD) of 8 newborn human brains, in comparison to 8 adult human brains. The estimates of the cell numbers were obtained using the stereological principles of the optical fractionator. In the case of the adults, the total number of neurons in the entire MD was an average of 41% lower than in the newborn, which was statistically highly significant (P < 0.001). The estimated average total number of neurons in MD thalamus of the newborns was 11.2 million (coefficient of variation [CV] = standard deviation/mean = 0.16), compared with the adults' 6.43 million (CV = 0.15). The glial cell numbers were substantially higher in the adult brains, with an increase of almost 4 times from 10.6 million at birth to 36.3 million in the fully developed adult brain. This is the first demonstration of a higher number of human neurons in the brain of newborns compared with the adult.

Metastability, criticality and phase transitions in brain and its models

This survey of experimental findings and theoretical insights of the past 25 years places the brain firmly into the conceptual framework of nonlinear dynamics, operating at the brink of criticality, which is achieved and maintained by self-organization. It is here the basis for proposing that the application of the twin concepts of scaling and universality of the theory of non-equilibrium phase transitions can serve as an informative approach for elucidating the nature of underlying neural-mechanisms, with emphasis on the dynamics of recursively reentrant activity flow in intracortical and cortico-subcortical neuronal loops.

Hierarchical control of dopamine neuron-firing patterns by nicotinic receptors

Nicotine elicits dopamine release by stimulating nicotinic acetylcholine receptors (nAChRs) on dopaminergic neurons. However, a modulation of these neurons by endogenous acetylcholine has not been described. We recorded, in vivo, the spontaneous activity of dopaminergic neurons in the VTA of anaesthetized wt and nAChR knockout mice and their response to nicotine injections. Deleting alpha7 or beta2 subunits modified the spontaneous firing patterns, demonstrating their direct stimulation by endogenous acetylcholine. Quantitative analysis further revealed four principal modes of firing, each depending on the expression of particular nAChR subunits and presenting unique responses to nicotine. The prominent role of the beta2 subunit was further confirmed by its selective lentiviral reexpression in the VTA. These data suggest a hierarchical control of dopaminergic neuron firing patterns by nAChRs: activation of beta2*-nAChR switches cells from a resting to an excited state, whereas activation of alpha7*-nAChRs finely tunes the latter state but only once beta2*-nAChRs have been activated.

Operational principles of neurocognitive networks

Large-scale neural networks are thought to be an essential substrate for the implementation of cognitive function by the brain. If so, then a thorough understanding of cognition is not possible without knowledge of how the large-scale neural networks of cognition (neurocognitive networks) operate. Of necessity, such understanding requires insight into structural, functional, and dynamical aspects of network operation, the intimate interweaving of which may be responsible for the intricacies of cognition. Knowledge of anatomical structure is basic to understanding how neurocognitive networks operate. Phylogenetically and ontogenetically determined patterns of synaptic connectivity form a structural network of brain areas, allowing communication between widely distributed collections of areas. The function of neurocognitive networks depends on selective activation of anatomically linked cortical and subcortical areas in a wide variety of configurations. Large-scale functional networks provide the cooperative processing which gives expression to cognitive function. The dynamics of neurocognitive network function relates to the evolving patterns of interacting brain areas that express cognitive function in real time. This article considers the proposition that a basic similarity of the structural, functional, and dynamical features of all neurocognitive networks in the brain causes them to function according to common operational principles. The formation of neural context through the coordinated mutual constraint of multiple interacting cortical areas, is considered as a guiding principle underlying all cognitive functions. Increasing knowledge of the operational principles of neurocognitive networks is likely to promote the advancement of cognitive theories, and to seed strategies for the enhancement of cognitive abilities.

Ongoing spontaneous activity controls access to consciousness: a neuronal model for inattentional blindness

Even in the absence of sensory inputs, cortical and thalamic neurons can show structured patterns of ongoing spontaneous activity, whose origins and functional significance are not well understood. We use computer simulations to explore the conditions under which spontaneous activity emerges from a simplified model of multiple interconnected thalamocortical columns linked by long-range, top-down excitatory axons, and to examine its interactions with stimulus-induced activation. Simulations help characterize two main states of activity. First, spontaneous gamma-band oscillations emerge at a precise threshold controlled by ascending neuromodulator systems. Second, within a spontaneously active network, we observe the sudden “ignition” of one out of many possible coherent states of high-level activity amidst cortical neurons with long-distance projections. During such an ignited state, spontaneous activity can block external sensory processing. We relate those properties to experimental observations on the neural bases of endogenous states of consciousness, and particularly the blocking of access to consciousness that occurs in the psychophysical phenomenon of “inattentional blindness,” in which normal subjects intensely engaged in mental activity fail to notice salient but irrelevant sensory stimuli. Although highly simplified, the generic properties of a minimal network may help clarify some of the basic cerebral phenomena underlying the autonomy of consciousness.

Computer simulations of the circuits of activity in the cerebral cortex and underlying thalamus suggest that precisely controlled oscillatory states can control the central neural processing of sensory information

Classification of hybrid crows in quail using artificial neural networks

In galliforms, calls are strongly determined genetically and no influence of learning has ever been demonstrated. Hybridization is a useful tool for investigating patterns of heritability. The vocal repertoire of the European quail (Coturnix c. coturnix) and of the Japanese quail (C. c. japonica) are similar except for their crows. The European quail possesses two forms of crows and the Japanese quail only one form. We produced hybrids from the following crosses; F(1), F(2) and backcrosses. Visual analysis of spectrograms showed that hybrid crows presented all intermediaries between the three forms of crows produced by the two subspecies. According to the level of analysis of a crow, visual classifications of spectrograms probably include some subjectivity. Artificial Neural Networks (ANN) are now widely used as a powerful classification technique in behavioural sciences. We trained an ANN to recognize the three crows of the two subspecies. Then we analysed its classification of hybrid crows. The ANN revealed important inter-individual variability between the crows of the F(1) and the F(2) crosses. Birds issued from backcrosses produced crows similar to those of the European quail to which they were backcrossed. This study confirms that ANN is a useful tool to classify spectrograms rapidly.

Delayed maturation and sensitive periods in the auditory cortex

Behavioral data indicate the existence of sensitive periods in the development of audition and language. Neurophysiological data demonstrate deficits in the cerebral cortex of auditory-deprived animals, mainly in reduced cochleotopy and deficits in corticocortical and corticothalamic loops. In addition to current spread in the cochlea, reduced cochleotopy leads to channel interactions after cochlear implantation. Deficits in corticocortical and corticothalamic loops interfere with normal processing of auditory activity in cortical areas. Thus, the deprived auditory cortex cannot mature normally in congenital deafness. This maturation can be achieved using auditory experience through cochlear implants. However, implantation is necessary within the sensitive period of the auditory system. The functional role of long-term potentiation and long-term depression, inhibition, cholinergic modulation and neurotrophins in auditory development and sensitive periods are discussed.

Reward-dependent learning in neuronal networks for planning and decision making

Neuronal network models have been proposed for the organization of evaluation and decision processes in prefrontal circuitry and their putative neuronal and molecular bases. The models all include an implementation and simulation of an elementary reward mechanism. Their central hypothesis is that tentative rules of behavior, which are coded by clusters of active neurons in prefrontal cortex, are selected or rejected based on an evaluation by this reward signal, which may be conveyed, for instance, by the mesencephalic dopaminergic neurons with which the prefrontal cortex is densely interconnected. At the molecular level, the reward signal is postulated to be a neurotransmitter such as dopamine, which exerts a global modulatory action on prefrontal synaptic efficacies, either via volume transmission or via targeted synaptic triads. Negative reinforcement has the effect of destabilizing the currently active rule-coding clusters; subsequently, spontaneous activity varies again from one cluster to another, giving the organism the chance to discover and learn a new rule. Thus, reward signals function as effective selection signals that either maintain or suppress currently active prefrontal representations as a function of their current adequacy. Simulations of this variation-selection have successfully accounted for the main features of several major tasks that depend on prefrontal cortex integrity, such as the delayed-response test, the Wisconsin card sorting test, the Tower of London test and the Stroop test. For the more complex tasks, we have found it necessary to supplement the external reward input with a second mechanism that supplies an internal reward; it consists of an auto-evaluation loop which short-circuits the reward input from the exterior. This allows for an internal evaluation of covert motor intentions without actualizing them as behaviors, by simply testing them covertly by comparison with memorized former experiences. This element of architecture gives access to enhanced rates of learning via an elementary process of internal or covert mental simulation. We have recently applied these ideas to a new model, developed with M. Kerszberg, which hypothesizes that prefrontal cortex and its reward-related connections contribute crucially to conscious effortful tasks. This model distinguishes two main computational spaces within the human brain: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative and attentional processors. We postulate that workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice; they selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously co-activated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. This model makes predictions concerning the spatio-temporal activation patterns during brain imaging of cognitive tasks, particularly concerning the conditions of activation of dorsolateral prefrontal cortex and anterior cingulate, their relation to reward mechanisms, and their specific reaction during error processing.

Computational models of association cortex

Recent computational models, or mathematical realizations of neurobiological theories, are providing insights into the organization and workings of the association cortex. Such models concern the construction of cortical maps, the neural basis of cognitive functions such as visual perception, reward-motivated learning and some aspects of consciousness.

Hierarchical neuronal modeling of cognitive functions: from synaptic transmission to the Tower of London

Recent progress in the molecular biology of synaptic transmission, in particular of neurotransmitter receptors, offers novel information relevant to 'realistic' modeling of neural processes at the single cell and network level. Sophisticated computer analyses of two-dimensional crystals by high resolution electron microscopy yield images of single neurotransmitter receptor molecules with tentative identifications of ligand binding sites and of conformational transitions. The dynamics of conformational changes can be accounted for by a 'multistate allosteric network' model. Allosteric receptors also possess the structural and functional properties required to serve as coincidence detectors between pre- and post-synaptic signals and, therefore, can be used as building blocks for a chemical Hebb synapse. These properties were introduced into networks of formal neurons capable of producing and detecting temporal sequences. In more elaborate models of pre-frontal cortex functions, allosteric receptors control the selection of transient 'pre-representations' and their stabilization by external or internal reward signals. We apply this scheme to Shallice's Tower of London test, and we show how a hierarchical neuronal architecture can implement executive or planning functions associated with frontal areas. (Académie des sciences/Elsevier, Paris.)