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

Clique of functional hubs orchestrates population bursts in developmentally regulated neural networks

It has recently been discovered that single neuron stimulation can impact network dynamics in immature and adult neuronal circuits. Here we report a novel mechanism which can explain in neuronal circuits, at an early stage of development, the peculiar role played by a few specific neurons in promoting/arresting the population activity. For this purpose, we consider a standard neuronal network model, with short-term synaptic plasticity, whose population activity is characterized by bursting behavior. The addition of developmentally inspired constraints and correlations in the distribution of the neuronal connectivities and excitabilities leads to the emergence of functional hub neurons, whose stimulation/deletion is critical for the network activity. Functional hubs form a clique, where a precise sequential activation of the neurons is essential to ignite collective events without any need for a specific topological architecture. Unsupervised time-lagged firings of supra-threshold cells, in connection with coordinated entrainments of near-threshold neurons, are the key ingredients to orchestrateComment: 39 pages, 15 figures, to appear in PLOS Computational Biolog

Enhanced pre-frontal functional-structural networks to support postural control deficits after traumatic brain injury in a pediatric population

Traumatic brain injury (TBI) affects the structural connectivity, triggering the re-organization of structural-functional circuits in a manner that remains poorly understood. We focus here on brain networks re-organization in relation to postural control deficits after TBI. We enrolled young participants who had suffered moderate to severeTBI, comparing them to young typically developing control participants. In comparison to control participants, TBI patients (but not controls) recruited prefrontal regions to interact with two separated networks: 1) a subcortical network including part of the motor network, basal ganglia, cerebellum, hippocampus, amygdala, posterior cingulum and precuneus; and 2) a task-positive network, involving regions of the dorsal attention system together with the dorsolateral and ventrolateral prefrontal regions

Toward fractioning of isomers through binding-induced acceleration of azobenzene switching

The E/Z isomerization process of a uracil-azobenzene derivative in which the nucleobase is conjugated to a phenyldiazene tail is studied in view of its ability to form triply-H-bonded complexes with a suitably complementary 2,6-diacetylamino-4-pyridine ligand. UV-Vis and 1H-NMR investigations of the photochemical and thermal isomerization kinetics show that the thermal Z→E interconversion is four-fold accelerated upon formation of the H-bonded complex. DFT calculations show that the formation of triple H-bonds triggers a significant elongation of the N=N double bond, caused by an increase of its πg∗ antibonding character. This results in a reduction of the N=N torsional barrier and thus in accelerated thermal Z→E isomerization. Combined with light controlled E→Z isomerization this enables controllable fractional tuning of the two configurational isomers

Hematopoietic Stem Cell Transplantation for Adult Acute Lymphoblastic Leukaemia

The most recent clinical trials on adult acute lymphoid leukaemia (ALL) have shown complete remission and disease-free survival (DFS) rates of 80-85% and 30-40%, respectively (Annino, et al, Durrant, et al, Kantarjian, et al, Larson, et al, Ribera, et al, Rowe). Intensified consolidation, particularly with high-dose methotrexate and high-dose cytarabine, may be one of the reasons for the improved outcome in recent series (Bassan and Hoelzer, Hoelzer and Gokbuget, Kebriaei and Larson). In addition, risk-adapted and subtype-oriented therapy may have contributed to this better outcome. However, the long term outcome of adult patients is still dismal, with approximately one third of the cases only being cured. At present, therapeutic options include conventional chemotherapy (CHT), high dose therapy with autologous and, especially, allogeneic stem cells transplantation (SCT) and, for certain subsets, such as BCR-ABL1+ ALL, specific targeted therapy (Piccaluga, et al). Although SCT has been used in adult ALL for more than 20 years, its role remains controversial as demonstrated by conflicting results in various studies. Previous casecontrolled studies did not show that allogeneic SCT (alloSCT) provided any advantage over CHT (Horowitz, et al, Zhang, et al) while in some studies there was an advantage, but restricted to young adults (Oh, et al). The number of controlled published or ongoing trials is remarkably small and some of them did not include both standard-risk and high-risk patients. Thus, it is difficult to draw definitive conclusions from their results. In fact, while some authors did not report any differences between alloSCT and chemotherapy or autologous SCT (ASCT)(Gupta, et al, Labar, et al), others only found differences favouring allogeneic SCT in standard risk (Goldstone, et al) or high-risk ALL patients (Sebban, et al, Thiebaut, et al, Thomas, et al). In this chapter, the Authors reviewed data concerning alloSCT in adult ALL and discuss current controversial and possible perspectives

A dataset of Visible – Short Wave InfraRed reflectance spectra collected in–vivo on the dorsal and ventral aspect of arms

Advancement of technology and device miniaturization have made near infrared spectroscopy (NIRS) techniques cost–effective, small–sized, simple, and ready to use. We applied NIRS to analyze healthy human muscles in vivo, and we found that this technique produces reliable and reproducible spectral “fingerprints” of individual muscles, that can be successfully discriminated by chemometric predictive models. The dataset presented in this descriptor contains the reflectance spectra acquired in vivo from the ventral and dorsal aspects of the arm using an ASD FieldSpec® 4 Standard–Res field portable spectroradiometer (350–2500 nm), the values of the anthropometric variables measured in each subject, and the codes to assist access to the spectral data. The dataset can be used as a reference set of spectral signatures of “biceps” and “triceps” and for the development of automated methods of muscle detection

Brain Mapping of Behavioral Domains Using Multi-Scale Networks and Canonical Correlation Analysis

Simultaneous mapping of multiple behavioral domains into brain networks remains a major challenge. Here, we shed some light on this problem by employing a combination of machine learning, structural and functional brain networks at different spatial resolutions (also known as scales), together with performance scores across multiple neurobehavioral domains, including sensation, motor skills, and cognition. Provided by the Human Connectome Project, we make use of three cohorts: 640 participants for model training, 160 subjects for validation, and 200 subjects for model performance testing thus enhancing prediction generalization. Our modeling consists of two main stages, namely dimensionality reduction in brain network features at multiple scales, followed by canonical correlation analysis, which determines an optimal linear combination of connectivity features to predict multiple behavioral performance scores. To assess the differences in the predictive power of each modality, we separately applied three different strategies: structural unimodal, functional unimodal, and multimodal, that is, structural in combination with functional features of the brain network. Our results show that the multimodal association outperforms any of the unimodal analyses. Then, to answer which human brain structures were most involved in predicting multiple behavioral scores, we simulated different synthetic scenarios in which in each case we completely deleted a brain structure or a complete resting state network, and recalculated performance in its absence. In deletions, we found critical structures to affect performance when predicting single behavioral domains, but this occurred in a lesser manner for prediction of multi-domain behavior. Overall, our results confirm that although there are synergistic contributions between brain structure and function that enhance behavioral prediction, brain networks may also be mutually redundant in predicting multidomain behavior, such that even after deletion of a structure, the connectivity of the others can compensate for its lack in predicting behavior.JC was funded by Ikerbasque: The Basque Foundation for Science and by the Department of Economic Development and Infrastructure of the Basque Country (Elkartek Program Grant KK-2021-00009). AJ-M was funded by a predoctoral contract from the Department of Education of the Basque Country Predoctoral Program PRE-2019-1-0070. IF-I was funded by a research assistant contract from the University of the Basque Country (Elkartek Program Grant KK-2021/00033). PB acknowledge financial support from Ikerbasque (The Basque Foundation for Science) and FEDER (AI-2021-039)

Near-Infrared Transflectance Spectroscopy Discriminates Solutions Containing Two Commercial Formulations of Botulinum Toxin Type A Diluted at Recommended Volumes for Clinical Reconstitution

: Botulinum neurotoxin type A (BoNT-A) is the active substance in pharmaceutical preparations widely used worldwide for the highly effective treatment of various disorders. Among the three commercial formulations of BoNT-A currently available in Italy for neurological indications, abobotulinum A toxin (Dysport\uae, Ipsen SpA, Milano, Italy) and incobotulinum A toxin (Xeomin\uae, Merz Pharma Italia srl, Milano, Italy) differ in the content of neurotoxin, non-toxic protein, and excipients. Clinical applications of BoNT-A adopt extremely diluted solutions (10-6 mg/mL) for injection in the target body district. Near-infrared spectroscopy (NIRS) and chemometrics allow rapid, non-invasive, and non-destructive methods for qualitative and quantitative analysis. No data are available to date on the chemometric analysis of the spectral fingerprints acquired from the diluted commercial formulations of BoNT-A. In this proof-of-concept study, we tested whether NIRS can categorize solutions of incobotulinum A toxin (lacking non-toxic proteins) and abobotulinum A toxin (containing non-toxic proteins). Distinct excipients in the two formulations were also analyzed. We acquired transmittance spectra in the visible and short-wave infrared regions (350-2500 nm) by an ASD FieldSpec 4\u2122 Standard-Res Spectrophotoradiometer, using a submerged dip probe designed to read spectra in transflectance mode from liquid samples. After preliminary spectra pre-processing, principal component analysis was applied to characterize the spectral features of the two BoNT-A solutions and those of the various excipients diluted according to clinical standards. Partial least squares-discriminant analysis was used to implement a classification model able to discriminate the BoNT-A solutions and excipients. NIRS distinguished solutions containing distinct BoNT-A commercial formulations (abobotulinum A toxin vs. incobotulinum A toxin) diluted at recommended volumes for clinical reconstitution, distinct proteins (HSA vs. incobotulinum A toxin), very diluted solutions of simple sugars (lactose vs. sucrose), and saline or water. Predictive models of botulinum toxin formulations were also performed with the highest precision and accuracy