Human Brain/Cloud Interface

The Internet comprises a decentralized global system that serves humanity’s collective effort to generate, process, and store data, most of which is handled by the rapidly expanding cloud. A stable, secure, real-time system may allow for interfacing the cloud with the human brain. One promising strategy for enabling such a system, denoted here as a “human brain/cloud interface” (“B/CI”), would be based on technologies referred to here as “neuralnanorobotics.” Future neuralnanorobotics technologies are anticipated to facilitate accurate diagnoses and eventual cures for the ∼400 conditions that affect the human brain. Neuralnanorobotics may also enable a B/CI with controlled connectivity between neural activity and external data storage and processing, via the direct monitoring of the brain’s ∼86 × 109 neurons and ∼2 × 1014 synapses. Subsequent to navigating the human vasculature, three species of neuralnanorobots (endoneurobots, gliabots, and synaptobots) could traverse the blood–brain barrier (BBB), enter the brain parenchyma, ingress into individual human brain cells, and autoposition themselves at the axon initial segments of neurons (endoneurobots), within glial cells (gliabots), and in intimate proximity to synapses (synaptobots). They would then wirelessly transmit up to ∼6 × 1016 bits per second of synaptically processed and encoded human–brain electrical information via auxiliary nanorobotic fiber optics (30 cm3) with the capacity to handle up to 1018 bits/sec and provide rapid data transfer to a cloud based supercomputer for real-time brain-state monitoring and data extraction. A neuralnanorobotically enabled human B/CI might serve as a personalized conduit, allowing persons to obtain direct, instantaneous access to virtually any facet of cumulative human knowledge. Other anticipated applications include myriad opportunities to improve education, intelligence, entertainment, traveling, and other interactive experiences. A specialized application might be the capacity to engage in fully immersive experiential/sensory experiences, including what is referred to here as “transparent shadowing” (TS). Through TS, individuals might experience episodic segments of the lives of other willing participants (locally or remote) to, hopefully, encourage and inspire improved understanding and tolerance among all members of the human family

From sensory cues to complex behaviour : towards an understanding of the neuronal computations underlying sensorimotor transformation in Caenorhabditis elegans

Tese de mestrado, Neurociências, Universidade de Lisboa, Faculdade de Medicina, 2020Sobrevivência em ambientes em rápida mudança requer mecanismos aprimorados que permitam aos organismos responder rapidamente a pistas sensoriais, captadas do meio envolvente, e a adaptarem o seu comportamento de forma adequada. O processamento, por parte do sistema nervoso dos organismos, dos mecanismos subjacentes a integração sensório-motora (a transformação de sinais sensoriais em outputs motores) e um dos processos mais fundamentais e, no entanto, mal compreendidos, em neurociências. Neste estudo, visou-se investigar de que forma o nemátodo Caenorhabditis elegans (C. elegans) efetua a transformação sensório-motora num dos seus principais circuitos neuronais de processamento de informação, fundamental na criação de comportamentos provocados pela perceção de odores. O conectoma de C. elegans foi minuciosamente estudado e mapeado, o que levou a que este nemátodo seja considerado um modelo biológico valioso para o estudo de circuitos neuronais e das suas funções. C. elegans e um organismo facilmente manipulável geneticamente. Transgenes que codificam indicadores de cálcio, como e exemplo GCaMP (genetically encoded calcium indicator), podem ser facilmente expressos em neurónios de interesse. GCaMP e uma variante de GFP (Green Fluorescent Protein) que sofre mudanças conformacionais mediante ligação a iões Ca2+ que fluem para o meio intracelular durante um evento de despolarização. Esta mudança conformacional provoca a emissão de fluorescência verde quando o organismo e iluminado com luz azul num setup de microscopia. A transparência de C. elegans torna indicadores de cálcio muito adequados para medição de atividade neuronal neste organismo. Com o advento de técnicas de microscopia para medição de atividade neuronal em C. elegans, foram desenvolvidos dispositivos microfluídicos que permitem manter o organismo imobilizado e sob condições ambientais controladas. A possibilidade de manter o ambiente exterior do organismo sob condições controladas permite o registo da atividade de neurónios específicos, ou mesmo de todo o sistema nervoso, em resolução single-cell, durante ambientes sensoriais constantes ou variáveis, permitindo a atribuição de padrões de atividade neuronal ao efeito de inputs sensoriais. De forma a quimiotaxar em direção a ambientes atrativos, C. elegans executa biased random walks, que consiste num aumento da duração de períodos de movimento dianteiro e uma diminuição na sequencia de manobras de reorientação. Executa também klinotaxis, o comportamento de oscilação da zona anterior do corpo em direções preferenciais, durante períodos de movimento dianteiro. Os princípios subjacentes as transformações sensório-motoras que influenciam o comportamento do organismo, de forma a causar um aumento ou diminuição da frequência de períodos de reversão, são ainda largamente desconhecidos. O interneurónio AIY e particularmente interessante para estudar estas questões, uma vez que este interneurónio recebe sinapses diretas de múltiplos neurónios sensoriais, e estabelece conexões reciprocas com vários neurónios, tendo estes funções na modulação da estratégia de locomoção. AIY foi previamente considerado como sendo fundamental e suficiente para a modulação de circuitos neuronais que, probabilisticamente, influenciam as principais estratégias comportamentais de C. elegans. Assim, estudar os mecanismos que estão na base da transformação sensório-motora que ocorre em AIY e da maior importância. Desta forma, será possível compreender os mecanismos empregados pelo sistema nervoso deste nemátodo, que codificam a execução de comportamentos fundamentais para a sua sobrevivência e fitness evolutivo: a habilidade de quimiotaxar em direção a ambientes sensoriais vantajosos. Em organismos que se movem livremente, o registo da atividade neuronal de células singulares com a gravação simultânea do comportamento do animal, permitiu estabelecer uma relação entre atividade neuronal e a execução de diferentes estratégias de locomoção, em múltiplos neurónios. Foi ainda observado, em estudos anteriores, que neurónios coativos em organismos imobilizados, estão também ativos durante o mesmo estado comportamental em animais que se movem livremente. Assim, a atividade de neurónios ativos em animais imobilizados pode ser diretamente relacionada com uma estratégia de locomoção. Embora o animal não esteja capaz de efetivar o comportamento codificado, um sinal de comando motor e gerado no sistema nervoso do animal. Desta forma, e possível compreender como e que o sistema nervoso do C. elegans combina estados comportamentais com inputs sensoriais, em animais imobilizados. Neurónios sensoriais em C. elegans possuem terminações nervosas expostas ao meio ambiente envolvente e podem reconhecem uma grande variedade de estímulos sensoriais. Neurónios motores enervam células musculares e são os neurónios ultimamente responsáveis pela geração de comportamentos. Interneurónios são considerados neurónios que carecem de terminações nervosas sensoriais ou juncões neuromusculares, por isso estabelecendo a comunicação entre neurónios sensoriais e motores ao formarem uma extensa rede de interações entre os últimos e outros interneurónios. Neste estudo, foram usadas técnicas de biologia molecular para expressar o indicador de cálcio GCaMP em neurónios de interesse: no interneurónio AIY; num dos seus principais parceiros pré-sinápticos – o neurónio sensorial AWC; e no interneurónio RIM. AWC e um neurónio sensorial envolvido na deteção de múltiplos odores, incluindo odor bacteriano. RIM e um interneurónio pré- motor cujos períodos de elevada atividade estão relacionados com a codificação de manobras de reversão. Foi utilizada microscopia confocal de disco giratório para registar a atividade dos neurónios acima mencionados, através das variações intracelulares de cálcio das células, tanto em animais imobilizados, como em animais livres. Observou-se que a atividade de AIY e aqui reportada como sendo dominada por um sinal codificante de estados de comando motor (locomoção dianteira/manobras de reversão), na ausência de mecanismos de feedback propriocetivo ativos. Apesar dos circuitos neuronais existentes no sistema nervoso de C. elegans, responsáveis pela sinalização do estado motor instantâneo para AIY, não serem dissecados, aqui e observada uma modulação da atividade do neurónio anterior a mudança de estado de comando motor. Esta observação e interpretada como uma indicação de que AIY regula a ocorrência de manobras de reversão. AIY recebe input maioritariamente de neurónios sensoriais, sendo, por isso, conhecido como um interneurónio primário. E, por isso, surpreendente encontrar uma regulação de estados de locomoção do animal numa fase tao precoce de transformação sensoriomotora. Estas descobertas vão de encontro a estudos recentes realizados em organismos com sistemas nervosos mais complexos. De seguida, visou-se compreender como e que o sinal dominante que governa a atividade de AIY e combinado com informação sensorial. Para isso, desenvolveu-se um paradigma de estimulação sensorial usando dispositivos microfluídicos que permitem o fornecimento de odores aos animais. Mediu-se a atividade de AWC e AIY em organismos imobilizados, enquanto se providenciou um estimulo sensorial de odor bacteriano. Devido a limitações técnicas do setup experimental usado para estimular o animal, não foi possível recapitular as respostas estereotipadas que o neurónio sensorial AWC apresenta aquando da estimulação sensorial, como reportado em literatura previa. Adicionalmente, não foram encontradas evidencias suficientes para afirmar que a atividade de AIY sofreu influencia do estimulo. Assim, não foi possível compreender em plenitude de que forma AIY combina informação de estados motores com informação sensorial. No entanto, encontrou-se evidencia para transformação sensório-motora, possivelmente através de outros circuitos neuronais que não o aqui estudado, que influenciou a modulação do comportamento animal. Estudos anteriores mostraram que AIY exibe atividade ao longo do axónio e suas projeções axonais, não existindo relatos de dinâmica de cálcio no núcleo ou corpo celular. Não e claro quão frequentemente neurónios mostram diferentes padrões de dinâmica de cálcio no soma ou neurites e, especificamente, quão frequentemente esta estratégia e usada por interneurónios como forma de integrar informação sensorial e motora no mesmo espaço celular. Não se encontrou evidencia de que esta estratégia e usada por AIY, sugerindo que este neurónio usa outras abordagens para combinar sinais de diferentes origens. Finalmente, a atividade de AWC e AIY for registada em animais livres de movimento, na presença de um gradiente bacteriano, uma fonte de alimento para C. elegans e, por isso, um forte estimulo sensorial. Atividade neuronal em animais restringidos de movimento e animais com a capacidade de se moverem livremente mostra diferenças. Deste modo, visou-se compreender como e que a atividade de AIY varia na presença de inputs sensoriais que só um animal livre de locomoção integra (inputs proprioceptivos). A fraca expressão de GCaMP que foi possível obter em AIY neste estudo limitou a resolução espacial e temporal dos dados obtidos, que revelaram ser insuficiente para os objetivos propostos. De um modo geral, este estudo e relevante para a comunidade por sugerir um interneurónio primário como sendo capaz de modular a ocorrência de estados de comando motor em estádios iniciais de integração sensório-motora. Esta estratégia foi recentemente reportada em sistemas nervosos mais complexos, sugerindo ter relevância funcional para múltiplos organismos do reino animal.Survival in fast changing environments requires fine-tuned mechanisms that allow the organisms to rapidly react to sensory cues and adapt their behaviour to respond accordingly. The brain’s computations underlying sensorimotor integration, the transformation of sensory signals into motor outputs, is one of the most fundamental, yet poorly understood, processes in neuroscience. Here, we aim to investigate how the nematode Caenorhabditis elegans achieves sensorimotor transformation, by studying one of its most fundamental neuronal circuits for information processing and odour evoked behaviours. By expressing genetically encoded calcium indicators in neurons of interest, we performed in vivo calcium imaging in immobilised worms, both in an environment deprived of fluctuating sensory stimulation and while delivering an attractive odour to the animals. We reveal the activity of a primary sensory neuron to be dominated by a signal encoding motor command states of the animal, and suggest that this neuron may take part in modulating motor command state transitions in the worm’s brain. Moreover, here, we aimed to study how an attractive cue for the worm affects the coding of behavioural states, and how a single neuron can multiplex both behavioural and sensory information. Finally, we recorded the activity of the same neurons in freely crawling animals as an attempt to understand how sensorimotor transformation varies from immobilised to unrestrained animals. Altogether, this work bears potential relevance to the C. elegans community by suggesting a primary sensory neuron as being capable of modulating motor commands states at early stages of sensorimotor transformation. This strategy has recently been reported in higher-order organisms as well, suggesting that it has functional relevance for organisms across the animal kingdom

Simulation of networks of spiking neurons: A review of tools and strategies

We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks.Comment: 49 pages, 24 figures, 1 table; review article, Journal of Computational Neuroscience, in press (2007

Oscillatory architecture of memory circuits

The coordinated activity between remote brain regions underlies cognition and memory function. Although neuronal oscillations have been proposed as a mechanistic substrate for the coordination of information transfer and memory consolidation during sleep, little is known about the mechanisms that support the widespread synchronization of brain regions and the relationship of neuronal dynamics with other bodily rhythms, such as breathing. During exploratory behavior, the hippocampus and the prefrontal cortex are organized by theta oscillations, known to support memory encoding and retrieval, while during sleep the same structures are dominated by slow oscillations that are believed to underlie the consolidation of recent experiences. The expression of conditioned fear and extinction memories relies on the coordinated activity between the mPFC and the basolateral amygdala (BLA), a neuronal structure encoding associative fear memories. However, to date, the mechanisms allowing this long-range network synchronization of neuronal activity between the mPFC and BLA during fear behavior remain virtually unknown. Using a combination of extracellular recordings and open- and closed-loop optogenetic manipulations, we investigated the oscillatory and coding mechanisms mediating the organization and coupling of the limbic circuit in the awake and asleep brain, as well as during memory encoding and retrieval. We found that freezing, a behavioral expression of fear, is tightly associated with an internally generated brain state that manifests in sustained 4Hz oscillatory dynamics in prefrontal-amygdala circuits. 4Hz oscillations accurately predict the onset and termination of the freezing state. These oscillations synchronize prefrontal-amygdala circuits and entrain neuronal activity to dynamically regulate the development of neuronal ensembles. This enables the precise timing of information transfer between the two structures and the expression of fear responses. Optogenetic induction of prefrontal 4Hz oscillations promotes freezing behavior and the formation of long-lasting fear memory, while closed-loop phase specific manipulations bidirectionally modulate fear expression. Our results unravel a physiological signature of fear memory and identify a novel internally generated brain state, characterized by 4Hz oscillations. This oscillation enables the temporal coordination and information transfer in the prefrontal-amygdala circuit via a phase-specific coding mechanism, facilitating the encoding and expression of fear memory. In the search for the origin of this oscillation, we focused our attention on breathing, the most fundamental and ubiquitous rhythmic activity in life. Using large-scale extracellular recordings from a number of structures, including the medial prefrontal cortex, hippocampus, thalamus, amygdala and nucleus accumbens in mice we identified and characterized the entrainment by breathing of a host of network dynamics across the limbic circuit. We established that fear-related 4Hz oscillations are a state-specific manifestation of this cortical entrainment by the respiratory rhythm. We characterized the translaminar and transregional profile of this entrainment and demonstrated a causal role of breathing in synchronizing neuronal activity and network dynamics between these structures in a variety of behavioral scenarios in the awake and sleep state. We further revealed a dual mechanism of respiratory entrainment, in the form of an intracerebral corollary discharge that acts jointly with an olfactory reafference to coordinate limbic network dynamics, such as hippocampal ripples and cortical UP and DOWN states, involved in memory consolidation. Respiration provides a perennial stream of rhythmic input to the brain. In addition to its role as the condicio sine qua non for life, here we provide evidence that breathing rhythm acts as a global pacemaker for the brain, providing a reference signal that enables the integration of exteroceptive and interoceptive inputs with the internally generated dynamics of the hippocampus and the neocortex. Our results highlight breathing, a perennial rhythmic input to the brain, as an oscillatory scaffold for the functional coordination of the limbic circuit, enabling the segregation and integration of information flow across neuronal networks

Towards a Dynamic Vision System - Computational Modelling of Insect Motion Sensitive Neural Systems

For motion perception, vision plays an irreplaceable role, which can extract more abundant useful movement features from an unpredictable dynamic environment compared to other sensing modalities. Nowadays, building a dynamic vision system for motion perception in a both reliable and efficient manner is still an open challenge. Millions of years of evolutionary development has provided, in nature, animals that possess robust vision systems capable of motion perception to deal with a variety of aspects of life. Insects, in particular, have a relatively smaller number of visual neurons compared to vertebrates and humans, but can still navigate smartly through visually cluttered and dynamic environments. Understanding the insects' visual processing pathways and methods thus are not only attractive to neural system modellers but also critical in providing effective solutions for future intelligent machines. Originated from biological researches in insect visual systems, this thesis investigates computational modelling of motion sensitive neural systems and potential applications to robotics. This proposes novel modelling of the locust and fly visual systems for sensing looming and translating stimuli. Specifically, the proposed models comprise collision selective neural networks of two lobula giant movement detectors (LGMD1 and LGMD2) in locusts, and translating sensitive neural networks of direction selective neurons (DSNs) in flies, as well as hybrid visual neural systems of their combinations. In all these proposed models, the functionality of ON and OFF pathways is highlighted, which separate visual processing into parallel computation. This works effectively to realise neural characteristics of both the LGMD1 and the LGMD2 in locusts and plays crucial roles in separating the different looming selectivity between the two visual neurons. Such a biologically plausible structure can also implement the fly DSNs for translational movements perception and guide fast motion tracking with a behavioural response to visual fixation. The effectiveness and flexibility of the proposed motion sensitive neural systems have been validated by systematic and comparative experiments ranging from off-line synthetic and real-world tests to on-line bio-robotic tests. The underlying characteristics and functionality of the locust LGMDs and the fly DSNs have been achieved by the proposed models. All the proposed visual models have been successfully realised on the embedded system in a vision-based ground mobile robot. The robot tests have verified the computational simplicity and efficiency of proposed bio-inspired methodologies, which hit at great potential of building neuromorphic sensors in autonomous machines for motion perception in a fast, reliable and low-energy manner

when channels cooperate or capacitance varies

Die elektrische Signalverarbeitung in Nervenzellen basiert auf deren erregbarer Zellmembran. Üblicherweise wird angenommen, dass die in der Membran eingebetteten leitfähigen Ionenkanäle nicht auf direkte Art gekoppelt sind und dass die Kapazität des von der Membran gebildeten Kondensators konstant ist. Allerdings scheinen diese Annahmen nicht für alle Nervenzellen zu gelten. Im Gegenteil, verschiedene Ionenkanäle “kooperieren” und auch die Vorstellung von einer konstanten spezifischen Membrankapazität wurde kürzlich in Frage gestellt. Die Auswirkungen dieser Abweichungen auf die elektrischen Eigenschaften von Nervenzellen ist das Thema der folgenden kumulativen Dissertationsschrift. Im ersten Projekt wird gezeigt, auf welche Weise stark kooperative spannungsabhängige Ionenkanäle eine Form von zellulärem Kurzzeitspeicher für elektrische Aktivität bilden könnten. Solche kooperativen Kanäle treten in der Membran häufig in kleinen räumlich getrennte Clustern auf. Basierend auf einem mathematischen Modell wird nachgewiesen, dass solche Kanalcluster als eine bistabile Leitfähigkeit agieren. Die dadurch entstehende große Speicherkapazität eines Ensembles dieser Kanalcluster könnte von Nervenzellen für stufenloses persistentes Feuern genutzt werden -- ein Feuerverhalten von Nutzen für das Kurzzeichgedächtnis. Im zweiten Projekt wird ein neues Dynamic Clamp Protokoll entwickelt, der Capacitance Clamp, das erlaubt, Änderungen der Membrankapazität in biologischen Nervenzellen zu emulieren. Eine solche experimentelle Möglichkeit, um systematisch die Rolle der Kapazität zu untersuchen, gab es bisher nicht. Nach einer Reihe von Tests in Simulationen und Experimenten wurde die Technik mit Körnerzellen des *Gyrus dentatus* genutzt, um den Einfluss von Kapazität auf deren Feuerverhalten zu studieren. Die Kombination beider Projekte zeigt die Relevanz dieser oft vernachlässigten Facetten von neuronalen Membranen für die Signalverarbeitung in Nervenzellen.Electrical signaling in neurons is shaped by their specialized excitable cell membranes. Commonly, it is assumed that the ion channels embedded in the membrane gate independently and that the electrical capacitance of neurons is constant. However, not all excitable membranes appear to adhere to these assumptions. On the contrary, ion channels are observed to gate cooperatively in several circumstances and also the notion of one fixed value for the specific membrane capacitance (per unit area) across neuronal membranes has been challenged recently. How these deviations from the original form of conductance-based neuron models affect their electrical properties has not been extensively explored and is the focus of this cumulative thesis. In the first project, strongly cooperative voltage-gated ion channels are proposed to provide a membrane potential-based mechanism for cellular short-term memory. Based on a mathematical model of cooperative gating, it is shown that coupled channels assembled into small clusters act as an ensemble of bistable conductances. The correspondingly large memory capacity of such an ensemble yields an alternative explanation for graded forms of cell-autonomous persistent firing – an observed firing mode implicated in working memory. In the second project, a novel dynamic clamp protocol -- the capacitance clamp -- is developed to artificially modify capacitance in biological neurons. Experimental means to systematically investigate capacitance, a basic parameter shared by all excitable cells, had previously been missing. The technique, thoroughly tested in simulations and experiments, is used to monitor how capacitance affects temporal integration and energetic costs of spiking in dentate gyrus granule cells. Combined, the projects identify computationally relevant consequences of these often neglected facets of neuronal membranes and extend the modeling and experimental techniques to further study them