| 1. |
- Abrams, M. B., et al.
(författare)
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A Standards Organization for Open and FAIR Neuroscience : the International Neuroinformatics Coordinating Facility
- 2021
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Ingår i: Neuroinformatics. - : Springer Nature. - 1539-2791 .- 1559-0089.
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Tidskriftsartikel (refereegranskat)abstract
- There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body.
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| 2. |
- Bahuguna, Jyotika, et al.
(författare)
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Homologous Basal Ganglia Network Models in Physiological and Parkinsonian Conditions
- 2017
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Ingår i: Frontiers in Computational Neuroscience. - : FRONTIERS MEDIA SA. - 1662-5188. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- The classical model of basal ganglia has been refined in recent years with discoveries of subpopulations within a nucleus and previously unknown projections. One such discovery is the presence of subpopulations of arkypallidal and prototypical neurons in external globus pallidus, which was previously considered to be a primarily homogeneous nucleus. Developing a computational model of these multiple interconnected nuclei is challenging, because the strengths of the connections are largely unknown. We therefore use a genetic algorithm to search for the unknown connectivity parameters in a firing rate model. We apply a binary cost function derived from empirical firing rate and phase relationship data for the physiological and Parkinsonian conditions. Our approach generates ensembles of over 1,000 configurations, or homologies, for each condition, with broad distributions for many of the parameter values and overlap between the two conditions. However, the resulting effective weights of connections from or to prototypical and arkypallidal neurons are consistent with the experimental data. We investigate the significance of the weight variability by manipulating the parameters individually and cumulatively, and conclude that the correlation observed between the parameters is necessary for generating the dynamics of the two conditions. We then investigate the response of the networks to a transient cortical stimulus, and demonstrate that networks classified as physiological effectively suppress activity in the internal globus pallidus, and are not susceptible to oscillations, whereas parkinsonian networks show the opposite tendency. Thus, we conclude that the rates and phase relationships observed in the globus pallidus are predictive of experimentally observed higher level dynamical features of the physiological and parkinsonian basal ganglia, and that the multiplicity of solutions generated by our method may well be indicative of a natural diversity in basal ganglia networks. We propose that our approach of generating and analyzing an ensemble of multiple solutions to an underdetermined network model provides greater confidence in its predictions than those derived from a unique solution, and that projecting such homologous networks on a lower dimensional space of sensibly chosen dynamical features gives a better chance than a purely structural analysis at understanding complex pathologies such as Parkinson's disease.
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| 3. |
- Balbi, P., et al.
(författare)
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A single Markov-type kinetic model accounting for the macroscopic currents of all human voltage-gated sodium channel isoforms
- 2017
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Ingår i: PloS Computational Biology. - : Public Library of Science. - 1553-734X .- 1553-7358. ; 13:9
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Tidskriftsartikel (refereegranskat)abstract
- Modelling ionic channels represents a fundamental step towards developing biologically detailed neuron models. Until recently, the voltage-gated ion channels have been mainly modelled according to the formalism introduced by the seminal works of Hodgkin and Huxley (HH). However, following the continuing achievements in the biophysical and molecular comprehension of these pore-forming transmembrane proteins, the HH formalism turned out to carry limitations and inconsistencies in reproducing the ion-channels electrophysiological behaviour. At the same time, Markov-type kinetic models have been increasingly proven to successfully replicate both the electrophysiological and biophysical features of different ion channels. However, in order to model even the finest non-conducting molecular conformational change, they are often equipped with a considerable number of states and related transitions, which make them computationally heavy and less suitable for implementation in conductance-based neurons and large networks of those. In this purely modelling study we develop a Markov-type kinetic model for all human voltage-gated sodium channels (VGSCs). The model framework is detailed, unifying (i.e., it accounts for all ion-channel isoforms) and computationally efficient (i.e. with a minimal set of states and transitions). The electrophysiological data to be modelled are gathered from previously published studies on whole-cell patch-clamp experiments in mammalian cell lines heterologously expressing the human VGSC subtypes (from NaV1.1 to NaV1.9). By adopting a minimum sequence of states, and using the same state diagram for all the distinct isoforms, the model ensures the lightest computational load when used in neuron models and neural networks of increasing complexity. The transitions between the states are described by original ordinary differential equations, which represent the rate of the state transitions as a function of voltage (i.e., membrane potential). The kinetic model, developed in the NEURON simulation environment, appears to be the simplest and most parsimonious way for a detailed phenomenological description of the human VGSCs electrophysiological behaviour.
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| 4. |
- Belic, Jovana, et al.
(författare)
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Corticostriatal circuits and their role in disease
- 2015
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Ingår i: Frontiers in Neuroscience. - Cairns, Australia : Frontiers Media SA. - 1662-4548 .- 1662-453X. ; 8, s. 31-
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Tidskriftsartikel (refereegranskat)abstract
- The basal ganglia (BG) represent subcortical structures considered to be involved in action selection and decision making [1]. Dysfunction of the BG circuitry leads to many motor and cognitive disorders such as Parkinson’s disease (PD), Tourette syndrome, Huntington’s disease, obsessive compulsive disorder and many others. Therefore, we simultaneously recorded local field potentials (LFPs) in primary motor cortex and sensorimotor striatum to study features directly related to healthy versus pathological states such as Parkinson disease and levodopa-induced dyskinesia [2], [3]. The striatum, the input stage of the basal ganglia (BG), is an inhibitory network that contains several distinct cell types and receives massive excitatory inputs from the cortex. Cortex sends direct projections to the striatum, while striatum can affect cortex only indirectly through other BG nuclei and thalamus. Firstly we analyzed spectral characteristics of the obtained signals and observed that during dyskinesia, the most prominent feature was a relative power increase in the high gamma frequency range around 80 Hz, while for PD it was the beta frequency range. Secondly our preliminary results have shown that during both pathological states effective connectivity in terms of Granger causality is bidirectional with an accent on striatal influence on cortex. In the case of dyskinesia we have also found a specifically high increase in effective connectivity at 80 Hz. In order to further understand the 80-Hz phenomenon we have performed cross-frequency analysis across all states and both structures and observed characteristic patterns in the case of dyskinesia in both structures but not in the case of PD and healthy state. We have seen a large relative decrease in the modulation of the amplitude at 80Hz by the phase of low frequency oscillations (up to ~10Hz). It has been suggested that the activity of local neural populations is modulated according to the global neuronal dynamics in the way that populations oscillate and synchronize at lower frequencies and smaller ensembles are active at higher frequencies Our results suggest unexpectedly a lack of coupling between the low frequency activity of a larger population and the synchronized activity of a smaller group of neurons active at 80Hz.
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| 5. |
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| 6. |
- Belic, Jovana, 1987-, et al.
(författare)
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Interactions in the Striatal Network with Different Oscillation Frequencies
- 2017
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Ingår i: Artificial Neural Networks and Machine Learning – ICANN. Lecture Notes in Computer Science. - Cham : Springer. - 9783319685991 ; , s. 129-136
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Konferensbidrag (refereegranskat)abstract
- Simultaneous oscillations in different frequency bands are implicated in the striatum, and understanding their interactions will bring us one step closer to restoring the spectral characteristics of striatal activity that correspond to the healthy state. We constructed a computational model of the striatum in order to investigate how different, simultaneously present, and externally induced oscillations propagate through striatal circuitry and which stimulation parameters have a significant contribution. Our results show that features of these oscillations and their interactions can be influenced via amplitude, input frequencies, and the phase offset between different external inputs. Our findings provide further untangling of the oscillatory activity that can be seen within the striatal network.
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| 7. |
- Belić, Jovana, 1987-, et al.
(författare)
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Interplay between periodic stimulation and GABAergic inhibition in striatal network oscillations
- 2017
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:4, s. 1-17
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Tidskriftsartikel (refereegranskat)abstract
- Network oscillations are ubiquitous across many brain regions. In the basal ganglia, oscillations are also present at many levels and a wide range of characteristic frequencies have been reported to occur during both health and disease. The striatum, the main input nucleus of the basal ganglia, receives massive glutamatergic inputs from the cortex and is highly susceptible to external oscillations. However, there is limited knowledge about the exact nature of this routing process and therefore, it is of key importance to understand how time-dependent, external stimuli propagate through the striatal circuitry. Using a network model of the striatum and corticostriatal projections, we try to elucidate the importance of specific GABAergic neurons and their interactions in shaping striatal oscillatory activity. Here, we propose that fast-spiking interneurons can perform an important role in transferring cortical oscillations to the striatum especially to those medium spiny neurons that are not directly driven by the cortical oscillations. We show how the activity levels of different populations, the strengths of different inhibitory synapses, degree of outgoing projections of striatal cells, ongoing activity and synchronicity of inputs can influence network activity. These results suggest that the propagation of oscillatory inputs into the medium spiny neuron population is most efficient, if conveyed via the fast-spiking interneurons. Therefore, pharmaceuticals that target fast-spiking interneurons may provide a novel treatment for regaining the spectral characteristics of striatal activity that correspond to the healthy state.
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| 8. |
- Belic, Jovana, 1987-, et al.
(författare)
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Striatal processing of cortical neuronal avalanches – A computational investigation
- 2016
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Ingår i: International Conference on Artificial Neural Networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer. - 9783319447780 - 9783319447773 ; , s. 72-79
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Konferensbidrag (refereegranskat)abstract
- In the cortex, spontaneous neuronal avalanches can be characterized by spatiotemporal activity clusters with a cluster size distribution that follows a power law with exponent –1.5. Recordings in the striatum revealed that striatal activity was also characterized by spatiotemporal clusters that followed a power law distribution albeit, with significantly steeper slope, i.e., they lacked the large spatial clusters that are commonly expected for avalanche dynamics. In this study, we used computational modeling to investigate the influence of intrastriatal inhibition and corticostriatal interplay as important factors to understand the experimental findings and overall information transmission among these circuits.
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| 9. |
- Belic, Jovana, et al.
(författare)
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The role of striatal feedforward inhibition in propagation of cortical oscillations
- 2017
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Ingår i: BMC Neuroscience. - Antwerpen. - 1471-2202. ; 18, s. 91-91
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Tidskriftsartikel (refereegranskat)abstract
- Fast spiking interneurons (FSIs) and feedforward (FF) inhibition are a common property of neuronal networks throughout the brain and play crucial role in neural computations. For instance, in the cortex FF inhibition sets the window of temporal integration and spiking and thereby contributes to the control of firing rate and correlations [1]. In the striatum (the main input structure of the basal ganglia) despite their high firing rates and strong synapses, FSIs (comprise 1–2% of striatal neurons) do not seem to play a major role in controlling the firing of medium spiny neurons (MSNs; comprise 95% of striatal neurons) [2] and so far, it has not been possible to attribute a functional role to FSIs in the striatum. Here we use a spiking neuron network model in order to investigate how externally induced oscillations propagate through striatal circuitry. Recordings in the striatum have shown robust oscillatory activity that might be in fact cortical oscillations transmitted by the corticostriatal projections [3–5]. We propose that FSIs can perform an important role in transferring cortical oscillations to the striatum especially to those MSNs that are not directly driven by the cortical oscillations. Strong and divergent connectivity of FSIs implies that even weak oscillations in FSI population activity can be spread to the whole MSN population [6]. Further, we have identified multiple factors that influence the transfer of oscillations to MSNs. The variables such as the number of activated neurons, ongoing activity, connectivity, and synchronicity of inputs influence the transfer of oscillations by modifying the levels of feedforward and feedback inhibitions suggesting that the striatum can exploit different parameters to impact the transfer of oscillatory signals.References1. Isaacson, J. S., & Scanziani, M. (2011). How inhibition shapes cortical activity. Neuron, 72(2), 231–243. 2. Berke, J. D. (2011). Functional properties of striatal fast-spiking interneurons. Frontiers in systems neuroscience, 5.3. Belić, J. J., Halje, P., Richter, U., Petersson, P., & Kotaleski, J. H. (2016). Untangling cortico-striatal connectivity and cross-frequency coupling in L-DOPA-induced dyskinesia. Frontiers in systems neuroscience, 10.4. Berke, J. D. (2009). Fast oscillations in cortical‐striatal networks switch frequency following rewarding events and stimulant drugs. European Journal of Neuroscience, 30(5), 848–859.5. Boraud, T., Brown, P., Goldberg, J. A., Graybiel, A. M., & Magill, P. J. (2005). Oscillations in the basal ganglia: the good, the bad, and the unexpected. In The basal ganglia VIII (pp. 1–24). Springer US.6. Belić, J. J., Kumar, A., & Kotaleski, J. H. (2017). Interplay between periodic stimulation and GABAergic inhibition in striatal network oscillations. PloS one, 12(4), e0175135.
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| 10. |
- Belic, Jovana
(författare)
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Untangling Cortico-Striatal Circuitry and its Role in Health and Disease - A computational investigation
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The basal ganglia (BG) play a critical role in a variety of regular motor and cognitive functions. Many brain diseases, such as Parkinson’s diseases, Huntington’s disease and dyskinesia, are directly related to malfunctions of the BG nuclei. One of those nuclei, the input nucleus called the striatum, is heavily connected to the cortex and receives afferents from nearly all cortical areas. The striatum is a recurrent inhibitory network that contains several distinct cell types. About 95% of neurons in the striatum are medium spiny neurons (MSNs) that form the only output from the striatum. Two of the most examined sources of GABAergic inhibition into MSNs are the feedback inhibition (FB) from the axon collaterals of the MSNs themselves, and the feedforward inhibition (FF) via the small population (1-2% of striatal neurons) of fast spiking interneurons (FSIs). The cortex sends direct projections to the striatum, while the striatum can affect the cortex only indirectly through other BG nuclei and the thalamus. Understanding how different components of the striatal network interact with each other and influence the striatal response to cortical inputs has crucial importance for clarifying the overall functions and dysfunctions of the BG. In this thesis I have employed advanced experimental data analysis techniques as well as computational modelling, to study the complex nature of cortico-striatal interactions. I found that for pathological states, such as Parkinson’s disease and L-DOPA-induced dyskinesia, effective connectivity is bidirectional with an accent on the striatal influence on the cortex. Interestingly, in the case of L-DOPA-induced dyskinesia, there was a high increase in effective connectivity at ~80 Hz and the results also showed a large relative decrease in the modulation of the local field potential amplitude (recorded in the primary motor cortex and sensorimotor striatum in awake, freely behaving, 6-OHDA lesioned hemi-parkinsonian rats) at ~80 Hz by the phase of low frequency oscillations. These results suggest a lack of coupling between the low frequency activity of a presumably larger neuronal population and the synchronized activity of a presumably smaller group of neurons active at 80 Hz. Next, I used a spiking neuron network model of the striatum to isolate the mechanisms underlying the transmission of cortical oscillations to the MSN population. I showed that FSIs play a crucial role in efficient propagation of cortical oscillations to the MSNs that did not receive direct cortical oscillations. Further, I have identified multiple factors such as the number of activated neurons, ongoing activity, connectivity, and synchronicity of inputs that influenced the transfer of oscillations by modifying the levels of FB and FF inhibitions. Overall, these findings reveal a new role of FSIs in modulating the transfer of information from the cortex to striatum. By modulating the activity and properties of the FSIs, striatal oscillations can be controlled very efficiently. Finally, I explored the interactions in the striatal network with different oscillation frequencies and showed that the features of those oscillations, such as amplitude and frequency fluctuations, can be influenced by a change in the input intensities into MSNs and FSIs and that these fluctuations are also highly dependent on the selected frequencies in addition to the phase offset between different cortical inputs. Lastly, I investigated how the striatum responds to cortical neuronal avalanches. Recordings in the striatum revealed that striatal activity was also characterized by spatiotemporal clusters that followed a power law distribution albeit, with significantly steeper slope. In this study, an abstract computational model was developed to elucidate the influence of intrastriatal inhibition and cortico-striatal interplay as important factors to understand the experimental findings. I showed that one particularly high activation threshold of striatal nodes can reproduce a power law-like distribution with a coefficient similar to the one found experimentally. By changing the ratio of excitation and inhibition in the cortical model, I saw that increased activity in the cortex strongly influenced striatal dynamics, which was reflected in a less negative slope of cluster size distributions in the striatum. Finally, when inhibition was added to the model, cluster size distributions had a prominently earlier deviation from the power law distribution compared to the case when inhibition was not present.
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