Revealing ensemble state transition patterns in multi-electrode neuronal recordings using hidden Markov models

In order to harness the computational capacity of dissociated cultured neuronal networks, it is necessary to understand neuronal dynamics and connectivity on a mesoscopic scale. To this end, this paper uncovers dynamic spatiotemporal patterns emerging from electrically stimulated neuronal cultures using hidden Markov models (HMMs) to characterize multi-channel spike trains as a progression of patterns of underlying states of neuronal activity. However, experimentation aimed at optimal choice of parameters for such models is essential and results are reported in detail. Results derived from ensemble neuronal data revealed highly repeatable patterns of state transitions in the order of milliseconds in response to probing stimuli

Brainstem Steering of Locomotor Activity in the Newborn Rat

International audienceControl of locomotion relies on motor loops conveying modulatory signals between brainstem and spinal motor circuits. We investigated the steering control of the brainstem reticular formation over the spinal locomotor networks using isolated brainstem-spinal cord preparations of male and female neonatal rats. First, we performed patch-clamp recordings of identified reticulospinal cells during episodes of fictive locomotion. This revealed that a spinal ascending phasic modulation of reticulospinal cell activity is already present at birth. Half of the cells exhibited tonic firing during locomotion, while the other half emitted phasic discharges of action potentials phase locked to ongoing activity. We next showed that mimicking the phasic activity of reticulospinal neurons by applying patterned electrical stimulation bilaterally at the ventral caudal medulla level triggered fictive locomotion efficiently. Moreover, the brainstem stimuli-induced locomotor rhythm was entrained in a one-to-one coupling over a range of cycle periods (2-6 s). Additionally, we induced turning like motor outputs by either increasing or decreasing the relative duration of the stimulation trains on one side of the brainstem compared to the other. The ability of the patterned descending command to control the locomotor output depended on the functional integrity of ventral reticulospinal pathways and the involvement of local spinal central pattern generator circuitry. Altogether, this study provides a mechanism by which brainstem reticulospinal neurons relay steering and speed commands to the spinal locomotor networks

Identification and neuromodulation of brain states to promote recovery of consciousness

Experimental and clinical studies of consciousness identify brain states (i.e., transient, relevant features of the brain associated with the state of consciousness) in a non-systematic manner and largely independent from the research into the induction of state changes. In this narrative review with a focus on patients with a disorder of consciousness (DoC), we synthesize advances on the identification of brain states associated with consciousness in animal models and physiological (sleep), pharmacological (anesthesia) and pathological (DoC) states of altered consciousness in human. We show that in reduced consciousness the frequencies in which the brain operates are slowed down and that the pattern of functional communication in the brain is sparser, less efficient, and less complex. The results also highlight damaged resting state networks, in particular the default mode network, decreased connectivity in long-range connections and in the thalamocortical loops. Next, we show that therapeutic approaches to treat DoC, through pharmacology (e.g., amantadine, zolpidem), and (non-)invasive brain stimulation (e.g., transcranial current stimulation, deep brain stimulation) have shown some effectiveness to promote consciousness recovery. It seems that these deteriorated features of conscious brain states may improve in response to these neuromodulation approaches, yet, targeting often remains non-specific and does not always lead to (behavioral) improvements. Furthermore, in silico model-based approaches allow the development of personalized assessment of the effect of treatment on brain-wide dynamics. Although still in infancy, the fields of brain state identification and neuromodulation of brain states in relation to consciousness are showing fascinating developments that, when united, might propel the development of new and better targeted techniques for DoC. For example, brain states could be identified in a predictive setting, and the theoretical and empirical testing (i.e., in animals, under anesthesia and patients with a DoC) of neuromodulation techniques to promote consciousness could be investigated. This review further helps to identify where challenges and opportunities lay for the maturation of brain state research in the context of states of consciousness. Finally, it aids in recognizing possibilities and obstacles for the clinical translation of these diagnostic techniques and neuromodulation treatment options across both the multi-modal and multi-species approaches outlined throughout the review. This paper presents interactive figures, supported by the Live Paper initiative of the Human Brain Project, enabling the interaction with data and figures illustrating the concepts in the paper through EBRAINS (go to https://wiki.ebrains.eu/bin/view/Collabs/live-paper-states-altered-consciousness and get started with an EBRAINS account).NA is research fellow, OG is Research Associate, and SL is research director at FRS-FNRS. JA is postdoctoral fellow at the FWO. The study was further supported by the University and University Hospital of Liège, the BIAL Foundation, the Belgian National Funds for Scientific Research (FRS-FNRS), the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3), the FNRS PDR project (T.0134.21), the ERA-Net FLAG-ERA JTC2021 project ModelDXConsciousness (Human Brain Project Partnering Project), the fund Generet, the King Baudouin Foundation, the Télévie Foundation, the European Space Agency (ESA) and the Belgian Federal Science Policy Office (BELSPO) in the framework of the PRODEX Programme, the Public Utility Foundation 'Université Européenne du Travail', "Fondazione Europea di Ricerca Biomedica", the BIAL Foundation, the Mind Science Foundation, the European Commission, the Fondation Leon Fredericq, the Mind-Care foundation, the DOCMA project (EU-H2020-MSCA–RISE–778234), the National Natural Science Foundation of China (Joint Research Project 81471100) and the European Foundation of Biomedical Research FERB Onlus

Nociception-induced spatial and temporal plasticity of synaptic connection and function in the hippocampal formation of rats: a multi-electrode array recording

<p>Abstract</p> <p>Background</p> <p>Pain is known to be processed by a complex neural network (neuromatrix) in the brain. It is hypothesized that under pathological state, persistent or chronic pain can affect various higher brain functions through ascending pathways, leading to co-morbidities or mental disability of pain. However, so far the influences of pathological pain on the higher brain functions are less clear and this may hinder the advances in pain therapy. In the current study, we studied spatiotemporal plasticity of synaptic connection and function in the hippocampal formation (HF) in response to persistent nociception.</p> <p>Results</p> <p>On the hippocampal slices of rats which had suffered from persistent nociception for 2 h by receiving subcutaneous bee venom (BV) or formalin injection into one hand paw, multisite recordings were performed by an 8 × 8 multi-electrode array probe. The waveform of the field excitatory postsynaptic potential (fEPSP), induced by perforant path electrical stimulation and pharmacologically identified as being activity-dependent and mediated by ionotropic glutamate receptors, was consistently positive-going in the dentate gyrus (DG), while that in the CA1 was negative-going in shape in naïve and saline control groups. For the spatial characteristics of synaptic plasticity, BV- or formalin-induced persistent pain significantly increased the number of detectable fEPSP in both DG and CA1 area, implicating enlargement of the synaptic connection size by the injury or acute inflammation. Moreover, the input-output function of synaptic efficacy was shown to be distinctly enhanced by the injury with the stimulus-response curve being moved leftward compared to the control. For the temporal plasticity, long-term potentiation produced by theta burst stimulation (TBS) conditioning was also remarkably enhanced by pain. Moreover, it is strikingly noted that the shape of fEPSP waveform was drastically deformed or split by a TBS conditioning under the condition of persistent nociception, while that in naïve or saline control state was not affected. All these changes in synaptic connection and function, confirmed by the 2-dimentional current source density imaging, were found to be highly correlated with peripheral persistent nociception since pre-blockade of nociceptive impulses could eliminate all of them. Finally, the initial pharmacological investigation showed that AMPA/KA glutamate receptors might play more important roles in mediation of pain-associated spatiotemporal plasticity than NMDA receptors.</p> <p>Conclusion</p> <p>Peripheral persistent nociception produces great impact upon the higher brain structures that lead to not only temporal plasticity, but also spatial plasticity of synaptic connection and function in the HF. The spatial plasticity of synaptic activities is more complex than the temporal plasticity, comprising of enlargement of synaptic connection size at network level, deformed fEPSP at local circuit level and, increased synaptic efficacy at cellular level. In addition, the multi-synaptic model established in the present investigation may open a new avenue for future studies of pain-related brain dysfunctions at the higher level of the neuromatrix.</p

Bursti-tunnistusmenetelmät ihmisperäisistä monikykyisistä kantasoluista erilaistetuille hermosoluverkostoille

A burst is a set of subsequent action potentials that are fired at a high frequency. Although bursts are a fundamental part of electrical activity of neuronal networks in vitro, no standardized method exists for burst detection. Visual identification of bursts is a widely accepted method, but it is not objective nor time-efficient. Therefore, various algorithms have been developed for burst detection. Burst detection algorithms are typically developed and verified only on one specific type of data. This can be problematic because the bursting activity is highly variable between different cell types. Consequently, the applicability of the algorithms is restricted to a narrow range of activity types. Especially applicability to human neuronal networks is questionable because the algorithms are often developed on rodent neuronal networks, which display distinct activity patterns in comparison to human networks. The aim of this thesis was to produce a test data set, which would well represent bursting and non-bursting activity observed in human pluripotent stem cell (hPSC)-derived neuronal networks, and to identify a single algorithm with optimal parameters that would successfully detect the bursts in this test data set. As rodent neuronal networks are also widely used in neuroscience, the algorithm was desired to function also on activity derived from rodent cultures. To achieve these goals, hESCs were differentiated into functional neuronal networks and cultured on microelectrode array (MEA). Primary rat cortical neurons were similarly cultured on MEA. Electrical activity of the developing networks was recorded twice a week until synchronized bursting emerged. At this point, pharmacological assays were performed in order to record modulated activity. On the MEA recordings, distinct activity patterns were identified, and short recordings representative of the distinct patterns were included to the test data set. The performance of four contemporary burst detection algorithms was evaluated on the test data set. The evaluation was based on visual identification of bursts from the raw MEA signal. For each algorithm, a performance score was determined and sensitivity and specificity were computed. The evaluation was performed in two runs using either 3 or 5 as minimum number of spikes required for a burst. Other algorithm parameters were set to default values suggested by the original authors. The optimization possibilities were not encouraging for other algorithms but logISI, which also provided the highest performance and the most balanced sensitivity and specificity values. Parameters of logISI were optimized for the test data set, which significantly improved its performance. As a result, logISI displayed good or excellent performance on the test data obtained from human and rat neuronal networks during spontaneous and pharmacologically modulated activity. Based on these results, logISI could have the potential to become a standard burst detection algorithm in the field.Bursti (engl. burst) on peräkkäisten korkealla taajuudella esiintyvien toimintapotentiaalien ryhmä. Vaikka burstit ovat olennainen osa maljalla kasvatettujen hermosoluverkostojen sähköistä aktiivisuutta, ei niiden tunnistukseen ole standardimenetelmää. Visuaalinen bursti-tunnistus on laajasti hyväksytty menetelmä, mutta se ei ole objektiivinen eikä ajallisesti tehokas. Tästä syystä bursti-tunnistukseen on kehitetty useita algoritmeja. Tyypillisesti nämä algoritmit on kehitetty ja niiden toiminta on varmennettu vain tietyn tyyppisellä datalla. Tämä voi olla ongelmallista, koska bursti-aktiivisuus eri solutyyppien välillä on vaihtelevaa. Näin ollen algoritmien soveltaminen on rajoitettu vain pieneen osaan aktiivisuustyyppejä. Erityisesti algoritmien soveltaminen ihmisperäisiin hermosoluverkostoihin on kyseenalaista, sillä algoritmit on usein kehitetty jyrsijäperäisillä hermosoluverkostoilla, joiden aktiivisuustyypit eroavat ihmisperäisisten hermosoluverkostojen aktiivisuustyypeistä. Tämän työn tavoitteena oli kerätä testiaineisto, joka sisältäisi monikykyisistä ihmisen kantasoluista erilaistetuissa hermosoluverkostoissa havaittavat burstaavat ja ei-burstaavat aktiviisuustyypit, sekä löytää tällä testiaineistolla toimiva algoritmi ja optimaaliset arvot sen muuttujille. Koska jyrsijäperäiset hermosoluverkostot ovat neurotieteissä paljon käytettyjä, valitun algoritmin haluttiin toimivan myös niistä peräisin olevalla aineistolla. Tavoitteen saavuttamiseksi ihmisperäisistä alkion kantasoluista erilaistettiin toiminnallisia hermosoluverkostoja, joita viljeltiin mikroelektrodihilan (engl. microelectrode array, MEA) päällä. Rotan eristettyjä aivokuoren hermosoluja viljeltiin samoin MEA:lla. Hermosoluverkostojen sähköistä aktiivisuutta mitattiin niiden kehityksen aikana kahdesti viikossa, kunnes havaittiin synkronista bursti-aktiivisuutta. Synkronisen bursti-aktiivisuuden ilmaannuttua suoritettiin farmakologiset testit ja mitattiin näin muunneltua aktiivisuutta. Saaduista MEA-mittauksista etsittiin erilaisia aktiivisuustyyppejä, joista muodostettiin testiaineisto. Neljän nykyaikaisen algoritmin toimintaa arvioitiin tässä testiaineistossa. Arviointi tehtiin vertailemalla algoritmien tuloksia raakasignaalista tehdyn visuaalisen bursti-tunnistuksen tuloksiin. Jokaisen algoritmin suoritus pisteytettiin ja niiden herkkyys ja tarkkuus laskettiin. Suoritusta arvioitiin kahdesti siten, että burstin vähimmäispiikkimäärä asetettiin ensin kolmeen ja sitten viiteen. Muiden muuttujien arvot asetettiin algoritmien kehittäjien alkuperäisten suositusten mukaisesti. Optimointi- mahdollisuudet olivat lupaavat vain logISI-algoritmille, joka myös suoriutui parhaiten ja jonka herkkyys ja tarkkuus olivat parhaassa tasapainossa. LogISI:n muuttujat optimoitiin testiaineistolle, mikä huomattavasti paransi sen suoritusta kyseisessä aineistossa. Optimoidulla logISI:llä saatiin joko hyvä tai erinomainen tulos koko testiaineistolla, joka oli saatu mittaamalla spontaania ja farmakologisesti muunneltua aktiivisuutta sekä ihmisperäisistä kantasoluista erilaistetuista että rotan aivokuoresta eristetyistä hermosolu-verkostoista. Näiden tulosten perusteella logISI on potentiaalinen vaihtoehto bursti-tunnistuksen standardimetodiksi

Consciousness operates beyond the timescale for discerning time intervals: implications for Q-mind theories and analysis of quantum decoherence in brain

This paper presents in details how the subjective time is constructed by the brain cortex via reading packets of information called "time labels", produced by the right basal ganglia that act as brain timekeeper. Psychophysiological experiments have measured the subjective "time quanta" to be 40 ms and show that consciousness operates beyond that scale - an important result having profound implications for the Q-mind theory. Although in most current mainstream biophysics research on cognitive processes, the brain is modelled as a neural network obeying classical physics, Penrose (1989, 1997) and others have argued that quantum mechanics may play an essential role, and that successful brain simulations can only be performed with a quantum computer. Tegmark (2000) showed that make-or-break issue for the quantum models of mind is whether the relevant degrees of freedom of the brain can be sufficiently isolated to retain their quantum coherence and tried to settle the issue with detailed calculations of the relevant decoherence rates. He concluded that the mind is classical rather than quantum system, however his reasoning is based on biological inconsistency. Here we present detailed exposition of molecular neurobiology and define the dynamical timescale of cognitive processes linked to consciousness to be 10-15 ps showing that macroscopic quantum coherent phenomena in brain are not ruled out, and even may provide insight in understanding life, information and consciousness

Noninvasive imaging of receptor function: signal transduction pathways and physiological readouts

Intracellular signaling describes the process of information propagation from the cell surface to the location within the cell where a biological response is executed. Signaling pathways involve a complex network of interacting molecular species. It is obvious that information on the activation of individual pathways is highly relevant in biomedical research, both from a diagnostic point of view and for evaluating therapeutic interventions. Modern molecular imaging approaches are capable of providing such information in a temporo-spatially resolved manner. Two strategies can be pursued: imaging individual pathway molecules or targeting protein-protein interactions, which are key elements of the signaling networks. Assays such as fluorescence resonance energy transfer, two-hybrid, protein fragment complementation or protein splicing have been adapted to allow studies in live mice. The major issues in imaging signal transduction are sensitivity, as critical species occur at low concentration, and the fact that the processes targeted are intracellular, that is, exogenous probes have to cross the cell membrane. Currently, the majority of these imaging methods are based on genetic engineering approaches and are therefore confined to experimental studies in animals. Exogenous probes for targeting intracellular pathway molecules are being developed and may allow translation into the clinic

Role of cholinergic receptors in prefrontal activity of nonhuman primates during an oculomotor rule-based working memory task

The ability to flexibly react to our dynamic environment is a cardinal component of cognition and our human identity. Millions across the globe are affected by disorders of cognition, affecting their ability to live independently. Prefrontal cortex is required for optimal cognitive functioning, but its circuitry is often disrupted in conditions of impaired cognition. In addition, the cholinergic system is vital to optimal executive function, but this is disrupted in a number of conditions, including Alzheimer’s disease and schizophrenia. The actions of cholinergic receptors were explored in this project with local application of cholinergic compounds onto prefrontal neurons as rhesus monkeys performed a rule-based saccadic task that requires working memory maintenance. The antisaccade task is a useful probe of prefrontal cortex function that elicits errors in neuropsychiatric conditions. Some prefrontal neurons respond to different task aspects of the antisaccade task, e.g., discharging preferentially for one task rule over the other (pro- or antisaccades), and are thought to be involved in the circuitry for correct behavioural responses. Chapter 2 explored the effect of general stimulation of cholinergic receptors on rhesus PFC neuronal activity during antisaccade performance. In Chapter 3, newly developed cholinergic receptor subtype-specific compounds were utilized to examine the actions of muscarinic M1 receptor stimulation on prefrontal activity. Cortical oscillations are emerging as an important aspect of cognitive circuitry, such as during working memory maintenance. Chapter 4 examined the influence of local cholinergic receptor stimulation and blockade on the power of local field potential in different frequency bands. This project characterized the role of cholinergic receptors in prefrontal cortical neurons that were actively involved in cognitive circuitry. This and future work on the cholinergic influence on prefrontal cortex will provide insights into the altered cognitive functioning in Alzheimer’s disease and schizophrenia, which are also affected by disrupted cholinergic systems