Emergence of chimera-like states in prefrontal-cortex macaque intracranial recordings

Neural synchronization plays a crucial role in cog- nitive functions and in performing tasks as it facilitates the transmission of information among the various brain subregions, and thus their communication. In this paper, we use an approach for analyzing and quantifying the emergence of synchronization patterns used previously in the study of data from toy dynamical models, in neurophysiological signals from a macaque monkey and particularly, from prefrontal-cortex intracranial recordings. Specifically, we study the emergence of synchronization patterns in neural ensembles recorded in the macaque brain while the monkey is performing the same delayed saccade task successfully for a number of times. We quantify the emergence of chimera- like states, metastability and coalition entropy in the recordings coming from intracranial arrays implanted in the macaque’s brain. Our results show the emergence of spatio-temporal co- existing patterns of synchronized and desynchronized behavior, termed chimera-like states with small metastability during the stage where the target and the distractor appears on the screen and when the go cue appears on the screen for the monkey to report, namely the two most crucial stages of the trials to be termed successful. Finally, we perform a statistical hypothesis test on the calculated quantities over the successful trials and demonstrate that our findings are statistically significant in the sense that they cannot be attributed to randomness

Classes de dynamiques neuronales et correlations structurées par l'experience dans le cortex visuel.

Neuronal activity is often considered in cognitive neuroscience by the evoked response but most the energy used by the brain is devoted to the sustaining of ongoing dynamics in cortical networks. A combination of classification algorithms (K means, Hierarchical tree, SOM) is used on intracellular recordings of the primary visual cortex of the cat to define classes of neuronal dynamics and to compare it with the activity evoked by a visual stimulus. Those dynamics can be studied with simplified models (FitzHugh Nagumo, hybrid dynamical systems, Wilson Cowan) for which an analysis is presented. Finally, with simulations of networks composed of columns of spiking neurons, we study the ongoing dynamics in a model of the primary visual cortex and their effect on the response evoked by a stimulus. After a learning period during which visual stimuli are presented, waves of depolarization propagate through the network. The study of correlations in this network shows that the ongoing dynamics reflect the functional properties acquired during the learning period.L'activité neuronale est souvent considérée en neuroscience cognitive par la réponse évoquée mais l'essentiel de l'énergie consommée par le cerveau permet d'entretenir les dynamiques spontanées des réseaux corticaux. L'utilisation combinée d'algorithmes de classification (K means, arbre hirarchique, SOM) sur des enregistrements intracellulaires du cortex visuel primaire du chat nous permet de définir des classes de dynamiques neuronales et de les comparer l'activité évoquée par un stimulus visuel. Ces dynamiques peuvent être étudiées sur des systèmes simplifiés (FitzHugh-Nagumo, systèmes dynamiques hybrides, Wilson-Cowan) dont nous présentons l'analyse. Enfin, par des simulations de réseaux composés de colonnes de neurones, un modèle du cortex visuel primaire nous permet d'étudier les dynamiques spontanées et leur effet sur la réponse à un stimulus. Après une période d'apprentissage pendant laquelle des stimuli visuels sont presentés, des vagues de dépolarisation se propagent dans le réseau. L'étude des correlations dans ce réseau montre que les dynamiques spontanées reflètent les propriétés fonctionnelles acquises au cours de l'apprentissage

Critical bistability and large-scale synchrony in human brain dynamics

Neurophysiological dynamics of the brain, overt behaviours, and private experiences of the mind are co-emergent and co-evolving phenomena. An adult human brain contains ~100 billion neurons that are hierarchically organized into intricate networks of functional units comprised of interconnected neurons. It has been hypothesized that neurons within a functional unit communicate with each other or neurons from other units via synchronized activity. At any moment, cascades of synchronized activity from millions of neurons propagate through networks of all sizes, and the levels of synchronization wax and wane. How to understand cognitive functions or diseases from such rich dynamics poses a great challenge. The brain criticality hypothesis proposes that the brain, like many complex systems, optimize its performance by operating near a critical point of phase transition between disorder and order, which suggests complex brain dynamics be effectively studied by combining computational and empirical approaches. Hence, the brain criticality framework requires both classic reductionist and reconstructionist approaches. Reconstructionism in the current context refers to addressing the “Wholeness” of macro-level emergence due to fundamental mechanisms such as synchrony between neurons in the brain. This thesis includes five studies and aims to advance theory, empirical evidence, and methodology in the research of neuronal criticality and large-scale synchrony in the human brain. Study I: The classic criticality theory is based on the hypothesis that the brain operates near a continuous, second order phase transition between order and disorder in resource-conserving systems. This idea, however, cannot explain why the brain, a non-conserving system, often shows bistability, a hallmark of first order, discontinuous phase transition. We used computational modeling and found that bistability may occur exclusively within the critical regime so that the first-order phase transition emerged progressively with increasing local resource demands. We observed that in human resting-state brain activity, moderate α-band (11 Hz) bistability during rest predicts cognitive performance, but excessive resting-state bistability in fast (> 80 Hz) oscillations characterizes epileptogenic zones in patients’ brain. These findings expand the framework of brain criticality and show that near-critical neuronal dynamics involve both first- and second-order phase transitions in a frequency-, neuroanatomy-, and state-dependent manner. Study II: Long-range synchrony between cortical oscillations below ~100 Hz is pervasive in brain networks, whereas oscillations and broad-band activities above ~100 Hz have been considered to be strictly local phenomena. We showed with human intracerebral recordings that high-frequency oscillations (HFOs, 100−400 Hz) may be synchronized between brain regions separated by several centimeters. We discovered subject-specific frequency peaks of HFO synchrony and found the group-level HFO synchrony to exhibit laminar-specific connectivity and robust community structures. Importantly, the HFO synchrony was both transiently enhanced and suppressed in separate sub-bands during tasks. These findings showed that HFO synchrony constitutes a functionally significant form of neuronal spike-timing relationships in brain activity and thus a new mesoscopic indication of neuronal communication per se. Studies III: Signal linear mixing in magneto- (MEG) and electro-encephalography (EEG) artificially introduces linear correlations between sources and confounds the separability of cortical current estimates. This linear mixing effect in turn introduces false positives into synchrony estimates between MEG/EEG sources. Several connectivity metrics have been proposed to supress the linear mixing effects. We show that, although these metrics can remove false positives caused by instantaneous mixing effects, all of them discover false positive ghost interactions (SIs). We also presented major difficulties and technical concerns in mapping brain functional connectivity when using the most popular pairwise correlational metrics. Study IV and V: We developed a novel approach as a solution to the SIs problem. Our approach is to bundle observed raw edges, i.e., true interactions or SIs, into hyperedges by raw edges’ adjacency in signal mixing. We showed that this bundling approach yields hyperedges with optimal separability between true interactions while suffers little loss in the true positive rate. This bundling approach thus significantly decreases the noise in connectivity graphs by minimizing the false-positive to true-positive ratio. Furthermore, we demonstrated the advantage of hyperedge bundling in visualizing connectivity graphs derived from MEG experimental data. Hence, the hyperedges represent well the true cortical interactions that are detectable and dissociable in MEG/EEG sources. Taken together, these studies have advanced theory, empirical evidence, and methodology in the research of neuronal criticality and large-scale synchrony in the human brain. Study I provided modeling and empirical evidence for linking bistable criticality and the classic criticality hypothesis into a unified framework. Study II was the first to reveal HFO phase synchrony in large-scale neocortical networks, which was a fundamental discovery of long-range neuronal interactions on fast time-scale per se. Study III raised awareness of the ghost interaction (SI) problem for a critical view on reliable interpretation of MEG/EEG connectivity, and for the development of novel approaches to address the SI problem. Study IV offered a practical solution to the SI problem and opened a new avenue for mapping reliable MEG/EEG connectivity. Study V described the technical details of the hyperedge bundling approach, shared the source code and specified the simulation parameters used in Study IV.Ihmisaivojen neurofysiologinen dynamiikka, ihmisen käyttäytyminen, sekä yksityiset mielen kokemukset syntyvät ja kehittyvät rinnakkaisina ilmiöinä. Ihmisen aivot koostuvat ~100 miljardista hierarkisesti järjestäytyneestä hermosolusta, jotka toisiinsa kytkeytyneinä muodostavat monimutkaisen verkoston toiminnallisia yksiköitä. Hermosolujen aktiivisuuden synkronoitumisen on esitetty mahdollistavan neuronien välisen kommunikoinnin toiminnallisten yksiköiden sisällä sekä niiden välillä. Hetkenä minä hyvänsä, synkronoidun aktiivisuuden kaskadit etenevät aivojen erikokoisissa verkostoissa jatkuvasti heikentyen ja voimistuen. Kognitiivisten funktioiden ja erilaisten aivosairauksien ymmärtäminen tulkitsemalla aivojen rikasta dynamiikkaa on suuri haaste. Kriittiset aivot -hypoteesi ehdottaa aivojen, kuten monien muidenkin kompleksisten systeemien, optimoivan suorituskykyään operoimalla lähellä kriittistä pistettä järjestyksen ja epäjärjestyksen välissä, puoltaen sitä, että aivojen kompleksisia dynamiikoita voitaisiin tutkia yhdistämällä laskennallisia ja empiirisiä lähestymistapoja. Aivojen kriittisyyden viitekehys edellyttää perinteistä reduktionismia ja rekonstruktionismia. Erityisesti, rekonstruktionismi tähtää kuvaamaan aivojen makrotason “yhteneväisyyden” syntymistä perustavanlaatuisten mekaniikoiden, kuten aivojen toiminnallisten yksiköiden välisen synkronian avulla. Tämä väitöskirja sisältää viisi tutkimusta, jotka edistävät teoriaa, empiirisiä todisteita ja metodologiaa aivojen kriittisyyden ja laajamittaisen synkronian tutkimuksessa. Tutkimus I tarjosi mallinnuksia ja empiirisiä todisteita bistabiilin kriittisyyden ja klassisen kriittisyyden hypoteesien yhdistämiseksi yhdeksi viitekehykseksi. Tutkimus II oli ensimmäinen laatuaan paljastaen korkeataajuisten oskillaatioiden (high-frequency oscillation, HFO) vaihesynkronian laajamittaisissa neokortikaalisissa verkostoissa, mikä oli perustavanlaatuinen löytö pitkän matkan neuronaalisista vuorovaikutuksista nopeilla aikaskaaloilla. Tutkimus III lisäsi tietoisuutta aave-vuorovaikutuksien (spurious interactions, SI) ongelmasta MEG/EEG kytkeytyvyyden luotettavassa tulkinnassa sekä uudenlaisten menetelmien kehityksessä SI-ongelman ratkaisemiseksi. Tutkimus IV tarjosi käytännöllisen “hyperedge bundling” -ratkaisun SI-ongelmaan ja avasi uudenlaisen tien luotettavaan MEG/EEG kytkeytyvyyden kartoittamiseen. Tutkimus V kuvasi teknisiä yksityiskohtia hyperedge bundling -menetelmästä, jakoi menetelmän lähdekoodin ja täsmensi tutkimuksessa IV käytettyjä simulaatioparametreja. Yhdessä nämä tutkimukset ovat edistäneet teoriaa, empiirisiä todisteita ja metodologiaa neuronaalisen kriittisyyden sekä laajamittaisen synkronian hyödyntämisessä ihmisaivojen tutkimuksessa

Linear and nonlinear approaches to unravel dynamics and connectivity in neuronal cultures

[eng] In the present thesis, we propose to explore neuronal circuits at the mesoscale, an approach in which one monitors small populations of few thousand neurons and concentrates in the emergence of collective behavior. In our case, we carried out such an exploration both experimentally and numerically, and by adopting an analysis perspective centered on time series analysis and dynamical systems. Experimentally, we used neuronal cultures and prepared more than 200 of them, which were monitored using fluorescence calcium imaging. By adjusting the experimental conditions, we could set two basic arrangements of neurons, namely homogeneous and aggregated. In the experiments, we carried out two major explorations, namely development and disintegration. In the former we investigated changes in network behavior as it matured; in the latter we applied a drug that reduced neuronal interconnectivity. All the subsequent analyses and modeling along the thesis are based on these experimental data. Numerically, the thesis comprised two aspects. The first one was oriented towards a simulation of neuronal connectivity and dynamics. The second one was oriented towards the development of linear and nonlinear analysis tools to unravel dynamic and connectivity aspects of the measured experimental networks. For the first aspect, we developed a sophisticated software package to simulate single neuronal dynamics using a quadratic integrate–and–fire model with adaptation and depression. This model was plug into a synthetic graph in which the nodes of the network are neurons, and the edges connections. The graph was created using spatial embedding and realistic biology. We carried out hundreds of simulations in which we tuned the density of neurons, their spatial arrangement and the characteristics of the fluorescence signal. As a key result, we observed that homogeneous networks required a substantial number of neurons to fire and exhibit collective dynamics, and that the presence of aggregation significantly reduced the number of required neurons. For the second aspect, data analysis, we analyzed experiments and simulations to tackle three major aspects: network dynamics reconstruction using linear descriptions, dynamics reconstruction using nonlinear descriptors, and the assessment of neuronal connectivity from solely activity data. For the linear study, we analyzed all experiments using the power spectrum density (PSD), and observed that it was sufficiently good to describe the development of the network or its disintegration. PSD also allowed us to distinguish between healthy and unhealthy networks, and revealed dynamical heterogeneities across the network. For the nonlinear study, we used techniques in the context of recurrence plots. We first characterized the embedding dimension m and the time delay δ for each experiment, built the respective recurrence plots, and extracted key information of the dynamics of the system through different descriptors. Experimental results were contrasted with numerical simulations. After analyzing about 400 time series, we concluded that the degree of dynamical complexity in neuronal cultures changes both during development and disintegration. We also observed that the healthier the culture, the higher its dynamic complexity. Finally, for the reconstruction study, we first used numerical simulations to determine the best measure of ‘statistical interdependence’ among any two neurons, and took Generalized Transfer Entropy. We then analyzed the experimental data. We concluded that young cultures have a weak connectivity that increases along maturation. Aggregation increases average connectivity, and more interesting, also the assortativity, i.e. the tendency of highly connected nodes to connect with other highly connected node. In turn, this assortativity may delineates important aspects of the dynamics of the network. Overall, the results show that spatial arrangement and neuronal dynamics are able to shape a very rich repertoire of dynamical states of varying complexity.[cat] L’habilitat dels teixits neuronals de processar i transmetre informació de forma eficient depèn de les propietats dinàmiques intrínseques de les neurones i de la connectivitat entre elles. La present tesi proposa explorar diferents tècniques experimentals i de simulació per analitzar la dinàmica i connectivitat de xarxes neuronals corticals de rata embrionària. Experimentalment, la gravació de l’activitat espontània d’una població de neurones en cultiu, mitjançant una càmera ràpida i tècniques de fluorescència, possibilita el seguiment de forma controlada de l’activitat individual de cada neurona, així com la modificació de la seva connectivitat. En conjunt, aquestes eines permeten estudiar el comportament col.lectiu emergent de la població neuronal. Amb l’objectiu de simular els patrons observats en el laboratori, hem implementat un model mètric aleatori de creixement neuronal per simular la xarxa física de connexions entre neurones, i un model quadràtic d’integració i dispar amb adaptació i depressió per modelar l’ampli espectre de dinàmiques neuronals amb un cost computacional reduït. Hem caracteritzat la dinàmica global i individual de les neurones i l’hem correlacionat amb la seva estructura subjacent mitjançant tècniques lineals i no–lineals de series temporals. L’anàlisi espectral ens ha possibilitat la descripció del desenvolupament i els canvis en connectivitat en els cultius, així com la diferenciació entre cultius sans dels patològics. La reconstrucció de la dinàmica subjacent mitjançant mètodes d’incrustació i l’ús de gràfics de recurrència ens ha permès detectar diferents transicions dinàmiques amb el corresponent guany o pèrdua de la complexitat i riquesa dinàmica del cultiu durant els diferents estudis experimentals. Finalment, a fi de reconstruir la connectivitat interna hem testejat, mitjançant simulacions, diferents quantificadors per mesurar la dependència estadística entre neurona i neurona, seleccionant finalment el mètode de transferència d’entropia gereralitzada. Seguidament, hem procedit a caracteritzar les xarxes amb diferents paràmetres. Malgrat presentar certs tres de xarxes tipus ‘petit món’, els nostres cultius mostren una distribució de grau ‘exponencial’ o ‘esbiaixada’ per, respectivament, cultius joves i madurs. Addicionalment, hem observat que les xarxes homogènies presenten la propietat de disassortativitat, mentre que xarxes amb un creixent nivell d’agregació espaial presenten assortativitat. Aquesta propietat impacta fortament en la transmissió, resistència i sincronització de la xarxa

Serotonergic modulation of the ventral pallidum by 5HT1A, 5HT5A, 5HT7 AND 5HT2C receptors

Introduction: Serotonin's involvement in reward processing is controversial. The large number of serotonin receptor sub-types and their individual and unique contributions have been difficult to dissect out, yet understanding how specific serotonin receptor sub-types contribute to its effects on areas associated with reward processing is an essential step. Methods: The current study used multi-electrode arrays and acute slice preparations to examine the effects of serotonin on ventral pallidum (VP) neurons. Approach for statistical analysis: extracellular recordings were spike sorted using template matching and principal components analysis, Consecutive inter-spike intervals were then compared over periods of 1200 seconds for each treatment condition using a student’s t test. Results and conclusions: Our data suggests that excitatory responses to serotonin application are pre-synaptic in origin as blocking synaptic transmission with low-calcium aCSF abolished these responses. Our data also suggests that 5HT1a, 5HT5a and 5HT7 receptors contribute to this effect, potentially forming an oligomeric complex, as 5HT1a antagonists completely abolished excitatory responses to serotonin application, while 5HT5a and 5HT7 only reduced the magnitude of excitatory responses to serotonin. 5HT2c receptors were the only serotonin receptor sub-type tested that elicited inhibitory responses to serotonin application in the VP. These findings, combined with our previous data outlining the mechanisms underpinning dopamine's effects in the VP, provide key information, which will allow future research to fully examine the interplay between serotonin and dopamine in the VP. Investigation of dopamine and serotonins interaction may provide vital insights into our understanding of the VP's involvement in reward processing. It may also contribute to our understanding of how drugs of abuse, such as cocaine, may hijack these mechanisms in the VP resulting in sensitization to drugs of abuse

An investigation of multiple natural origins of religion

This study attempts to trace how religion could have originated in prehistory and antiquity, out of natural human and prehuman behaviour, without requiring the reality of the supernatural.Religion is here defined as beliefs, conceptions, practices and roles concerned with the putative supernatural. A variety of manifestations or elements of religious belief and practice can be identified. It is proposed that they have separate origins. Examples of religious elements are: life after death, ghosts, sacrifice, priests, shamans, gods, demons, .... It is argued that to try to reduce religion to one original element is a mistake. There may be no single origin. But the individual elements have origins, and plausible theories can account for each.Using theories and insights of previous workers, elaborated as necessary with information from a range of sciences, arguments are presented to account for five major foundational religious elements, thereby illustrating and partly fulfilling what is potentially a much wider programme. The elements covered are: (1) Animatism: numina, daemons; (2) Animism: ghosts, souls; (3) Another world: life after death; (4) Another world: heaven; (5) Religious specialists: shamans.Chapter 1 introduces the programme. Chapter 2 sets out definitions, philosophical principles and methodologyChapter 3 explores the specifically numinous quality which characterizes the supernatural in subjective experience. Chapter 4 describes brain structures and the neural substrate of experience. Chapter 5 proposes specific neurological hypotheses to account for certain types of numinous or `supernatural' experience.Chapter 6 deals with ape mentality, which may be presumed to characterize that of our remote ancestors, and identifies precursors of religious elements.Chapters 7 - 11 deal with the possibly separate origin of five major religious elements, as listed above.Chapter 12 summarizes the investigation, attempts to place the elements covered in sequence of their development in prehistory and antiquity, and expresses the limitations of the theory constructed

Psychophysiological evidence of a role for emotion in the learning of trustworthiness from identity-contingent eye-gaze cues

There is an increasing recognition that emotion influences cognition. This is particularly clear in the domain of social cognition where the perception of social cues is most often a potent source of emotional arousal. One process likely to be influenced by emotion is the forming of face evaluations. Judgements of trustworthiness are particularly important due to the potential costs and benefits of the decision to rely upon another person. Face trustworthiness is modulated by one particular social cue, eye-gaze. In reaction time tasks, when faces gaze away from target objects, incongruently, responses are slower than when faces gaze towards target objects, congruently. Faces that consistently gaze incongruently are also judged less trustworthy than faces that consistently gaze congruently.! In six experiments, we investigated the role of emotion in the learning of trustworthiness from identity-contingent gaze-cues using event-related potentials (ERP) and facial electromyography (EMG), which are sensitive electrophysiological measures of emotion. We found that the learning of trust was paralleled by an increase in the emotionrelated late positive potential (LPP) to incongruent faces across blocks. These findings were further supported by EMG measurements, which showed that corrugator muscle activity related to negative embodied emotional states, was greater to incongruent faces in those participants who showed expected changes in trust ratings. Although effects of gaze-cues on trust were consistent, they were not modulated by extremes in initial trust or priming of emotions elicited by social exclusion. Effects appeared to be due to a special relationship between faces, gaze, emotion and trust as the effects of validity on liking ratings were much weaker or non-existent compared to trust despite evidence of similar emotion-related LPP ERP and EMG activity. The effects also did not generalise to non-social arrow cues. In sum, we conclude that emotion mediates the learning of trust from identity-contingent gaze-cues