From neuronal networks to behavior: dynamics of spontaneous activity and onset of movement in the leech

Animal behavior was once seen as a chain of reactions to stimuli from the environment. From chemotaxis in bacteria to mammals withdrawing from painful stimuli, most of the actions taken by animals are clearly driven by external inputs. Reflexes were among the first phenomena to be studied to have an insight on the dynamics of the nervous system. Later, a step forward was the discovery of central pattern generators: once a behavior is started by a stimulus, some neuronal networks are able to maintain it without further inputs from the environment. The nervous system of all animals, however, is so complex that is displaying a rich dynamics even in the absence of external inputs or, in a more realistic situation, when no single input is able to drive a clear-cut reaction. In the same way, at the motor output level, animals keep moving in the absence of evident stimuli. These spontaneous behaviors are still far from being understood. Difficult problems are often easier to solve in simple systems. The leech has a relatively simple nervous system, composed of ~103 neurons disposed in a regular structure, but at the same time displays a variety of different behaviors. It seems then a good preparation to approach the spontaneous dynamics problem. The aim of my PhD research is to describe the spontaneous behavior of the leech and the spontaneous activity of its nervous system. A first, necessary step for this study was to develop a method of automatic classification and analysis of the leech movements. Thanks to this method we described accurately the properties of the different behaviors: we focused particularly on the largely unknown irregular exploratory behavior, which is found to display a broad range of oscillation frequencies and displacement speeds, but with some recurrent movement patterns. Finding the complete list of the leech spontaneous behaviors, and the probability of the transitions between them, it was possible to demonstrate that decision making in the leech is a Markovian process. The spontaneous activity in the isolated leech ganglion was found to be characterized by long-term correlations and a large variability in bursts size and duration. The same dynamics was observed in dissociated culture of rat hippocampal neurons, despite the difference in the structure between the two networks. We studied the effects of pharmacological modulations of inhibitory and excitatory processes on the spontaneous activity, and the role of single identified motor neurons in spontaneous bursts. Finally we proposed a simple statistical model accounting for experimental results. We studied then the spontaneous activity of the leech ganglion when it was connected to the other ganglia and in the semi-intact moving animal. Inputs received from the head and tail brain caused a drastic change in the activity of the ganglion, increasing synchronization among neurons and leading to a regime dominated by very large bursts. By recording at the same the movements of the leech and its nervous activity it was possible to have a better understanding of the relationship between the motor neuron bursts and the onset of movements

Spontaneous and evoked electrical activity of neurons in leech Hirudo medicinalis studied by a new generation of voltage sensitive dyes

By using the newly developed voltage sensitive dye VF2.1.Cl invented by Miller and colleagues (Miller et al. 2012), I monitored simultaneously the spontaneous electrical activity of approximately 80 neurons in a leech ganglion, representing around 20% of the entire neuronal population. Neurons imaged on the ventral surface of the ganglion either fired spikes regularly at a rate of 1-5 Hz or fired sparse spikes irregularly. In contrast, neurons imaged on the dorsal surface, fired spikes in bursts involving several neurons. The overall degree of correlated electrical activity among leech neurons was limited in control conditions but increased in the presence of the neuromodulator serotonin. The spontaneous electrical activity in a leech ganglion is segregated in three main groups: neurons comprising Retzius cells, Anterior Pagoda , Leydig and Annulus Erector motoneurons firing almost periodically, a group of neurons firing sparsely and randomly, and a group of neurons firing bursts of spikes of varying durations. These three groups interact and influence each other only weakly. I was able to obtain long optical recordings for several minutes. I studied, also, the evoked response of nervous system by stimulating mechanosensory neurons. This work paves the way for further studies of multicellular networks using the new voltage sensitive dye

Information processing in dissociated neuronal cultures of rat hippocampal neurons

One of the major aims of Systems Neuroscience is to understand how the nervous system transforms sensory inputs into appropriate motor reactions. In very simple cases sensory neurons are immediately coupled to motoneurons and the entire transformation becomes a simple reflex, in which a noxious signal is immediately transformed into an escape reaction. However, in the most complex behaviours, the nervous system seems to analyse in detail the sensory inputs and is performing some kind of information processing (IP). IP takes place at many different levels of the nervous system: from the peripheral nervous system, where sensory stimuli are detected and converted into electrical pulses, to the central nervous system, where features of sensory stimuli are extracted, perception takes place and actions and motions are coordinated. Moreover, understanding the basic computational properties of the nervous system, besides being at the core of Neuroscience, also arouses great interest even in the field of Neuroengineering and in the field of Computer Science. In fact, being able to decode the neural activity can lead to the development of a new generation of neuroprosthetic devices aimed, for example, at restoring motor functions in severely paralysed patients (Chapin, 2004). On the other side, the development of Artificial Neural Networks (ANNs) (Marr, 1982; Rumelhart & McClelland, 1988; Herz et al., 1981; Hopfield, 1982; Minsky & Papert, 1988) has already proved that the study of biological neural networks may lead to the development and to the design of new computing algorithms and devices. All nervous systems are based on the same elements, the neurons, which are computing devices which, compared to silicon components, are much slower and much less reliable. How are nervous systems of all living species able to survive being based on slow and poorly reliable components? This obvious and na\uefve question is equivalent to characterizing IP in a more quantitative way. In order to study IP and to capture the basic computational properties of the nervous system, two major questions seem to arise. Firstly, which is the fundamental unit of information processing: 2 single neurons or neuronal ensembles? Secondly, how is information encoded in the neuronal firing? These questions - in my view - summarize the problem of the neural code. The subject of my PhD research was to study information processing in dissociated neuronal cultures of rat hippocampal neurons. These cultures, with random connections, provide a more general view of neuronal networks and assemblies, not depending on the circuitry of a neuronal network in vivo, and allow a more detailed and careful experimental investigation. In order to record the activity of a large ensemble of neurons, these neurons were cultured on multielectrode arrays (MEAs) and multi-site stimulation was used to activate different neurons and pathways of the network. In this way, it was possible to vary the properties of the stimulus applied under a controlled extracellular environment. Given this experimental system, my investigation had two major approaches. On one side, I focused my studies on the problem of the neural code, where I studied in particular information processing at the single neuron level and at an ensemble level, investigating also putative neural coding mechanisms. On the other side, I tried to explore the possibility of using biological neurons as computing elements in a task commonly solved by conventional silicon devices: image processing and pattern recognition. The results reported in the first two chapters of my thesis have been published in two separate articles. The third chapter of my thesis represents an article in preparation

On the Dynamics of the Spontaneous Activity in Neuronal Networks

Most neuronal networks, even in the absence of external stimuli, produce spontaneous bursts of spikes separated by periods of reduced activity. The origin and functional role of these neuronal events are still unclear. The present work shows that the spontaneous activity of two very different networks, intact leech ganglia and dissociated cultures of rat hippocampal neurons, share several features. Indeed, in both networks: i) the inter-spike intervals distribution of the spontaneous firing of single neurons is either regular or periodic or bursting, with the fraction of bursting neurons depending on the network activity; ii) bursts of spontaneous spikes have the same broad distributions of size and duration; iii) the degree of correlated activity increases with the bin width, and the power spectrum of the network firing rate has a 1/f behavior at low frequencies, indicating the existence of long-range temporal correlations; iv) the activity of excitatory synaptic pathways mediated by NMDA receptors is necessary for the onset of the long-range correlations and for the presence of large bursts; v) blockage of inhibitory synaptic pathways mediated by GABA(A) receptors causes instead an increase in the correlation among neurons and leads to a burst distribution composed only of very small and very large bursts. These results suggest that the spontaneous electrical activity in neuronal networks with different architectures and functions can have very similar properties and common dynamics

Identification and Characterization of electrical patterns underlying stereotyped behaviours in the semi-intact leech

Neuroscience aims at understanding the mechanisms underlying perception, learning, memory, consciousness and acts. The present Ph.D. thesis aims to elucidate some principles controlling actions, which in a more scientific and technical language is referred to as motor control. This concept has been studied in a variety of preparations in vertebrate and invertebrate species. In this PhD thesis, the leech has been the subject of choice, because it is a well known preparation, highly suitable for relating functional and behavioural properties to the underlying neuronal networks. The semi-intact leech preparation (Kristan et al., 1974) has been the main methodological strategy performed in the experiments. Its importance lies in the fact that it gives the possibility to access the information from the leech\u2019s central nervous system (CNS) and compare simultaneously some stereotyped behaviours. Thus, entering in this work it is necessary to make a brief summary of the steps followed before arriving to the conclusions written ahead. The main objective followed in this work has been the analysis, identification and characterization of electrical patterns underlying different behaviours in Hirudo medicinalis. This main objective has been reached focusing the project on three particular objectives, which have been pursued during the author\u2019s Philosophical Doctorate course

Calcium dynamics and compartmentalization in leech neurons

The aim of this project was to study how and where action potentials arise and propagate in the arborizations of identified neurons in the central nervous system of the leech. A major aim was to assess whether the entry of calcium is localized to distinct regions of the cells and to determine whether there are significant differences in calcium channel distribution between different types of neurons. A combination of electrophysiological techniques, optical recording and image analysis was used to approach these problems. I developed an experimental set-up for optical recordings of calcium transients by a fast CCD-camera. By use of calcium sensitive dyes I analysed in detail optical responses to electrical stimulation of neurons and the density of calcium channels, spatially and temporarily, in different neural cell types, including mechanosensory neurons and motoneurons. Fluorescence changes ( 06F/F) of the membrane impermeable calcium indicator Oregon Green were measured. The dye was pressure injected into the soma of neurons under investigation. 06F/F caused by a single action potential (AP) in mechanosensory neurons had approximately the same amplitude and time course in the soma and in distal processes. By contrast, in other neurons such as the Anterior Pagoda neuron, the Annulus Erector motoneuron, the L motoneuron and other motoneurons, APs evoked by passing depolarizing current in the soma produced much larger fluorescence changes in distal processes than in the soma. When APs were evoked by stimulating one distal axon through the root, 06F/F was large in all distal processes, but very small in the soma. These results confirm and extend previous electrophysiological data which demonstrate that the soma of a motoneuron in the leech, as in many other invertebrates, does not generate action potentials (Stuart, 1970; Muller and Nicholls, 2 1974; Goodman and Heitler, 1979). Impulses recorded in the soma are normally only a few millivolts in amplitude. The AP of a motoneuron propagates to muscles of the body wall along segmental nerves that emerge from ganglia. The site of impulse initiation has been found to be at a distance from the soma but within the ganglion (Melinek and Muller, 1996; Gu et al. 1991). Our experiments with fluorescent transients are in accord with the concept that they result from calcium entry through voltage sensitive channels. Thus at sites where APs are found to be large, the calcium signals are large (as in peripheral axons), while at sites where spikes are small, (as in motoneuronal cell bodies) signals were weak, or non existent

Flexibility of neuronal codes:adaptation to stimulus statistics in a mechanosensorial neuron firing in bursts

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Anatomía, Histología y Neurociencia

Fractals in the Nervous System: conceptual Implications for Theoretical Neuroscience

This essay is presented with two principal objectives in mind: first, to document the prevalence of fractals at all levels of the nervous system, giving credence to the notion of their functional relevance; and second, to draw attention to the as yet still unresolved issues of the detailed relationships among power law scaling, self-similarity, and self-organized criticality. As regards criticality, I will document that it has become a pivotal reference point in Neurodynamics. Furthermore, I will emphasize the not yet fully appreciated significance of allometric control processes. For dynamic fractals, I will assemble reasons for attributing to them the capacity to adapt task execution to contextual changes across a range of scales. The final Section consists of general reflections on the implications of the reviewed data, and identifies what appear to be issues of fundamental importance for future research in the rapidly evolving topic of this review