| 1. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Kaur-Kahlon, G., et al.
(författare)
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Response of a coastal tropical pelagic microbial community to changed salinity and temperature
- 2016
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Ingår i: Aquatic Microbial Ecology. - 0948-3055 .- 1616-1564. ; 77:1, s. 37-50
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Tidskriftsartikel (refereegranskat)abstract
- Studies on the responses of tropical microbial communities to changing hydrographic conditions are presently poorly represented. We present here the results from a mesocosm experiment conducted in southwest (SW) coastal India to investigate how changes in temperature and salinity may affect a coastal tropic microbial community. The onset of algal and bacterial blooms, the maximum production and biomass, and the interrelation between phytoplankton and bacteria were studied in replicated mesocosms. The treatments were set up featuring ambient conditions (28 °C, 35 PSU), hyposalinity (31 PSU), warming (31 °C) and a double manipulated treatment with warming and hyposalinity (31 °C, 31 PSU). The hyposaline treatment had the most considerable influence manifested as significantly lower primary production, and the most dissimilar microphytoplankton species community. The increased temperature acted as a catalyst in the double manipulated treatment and higher primary production was maintained. We investigated the dynamics of the microbial community with a structural equation model approach, and found a significant interrelation between phytoplankton biomass and bacterial abundance. Using this methodology, it became evident that temperature and salinity changes, individually and together, mediate direct and indirect effects that influence different compartments of the microbial loop. In the face of climate change, we suggest that in relatively nutrient replete tropical coastal zones, salinity and temperature changes will affect nutrient assimilation with subsequent significant effects on the quantity of microbial biomass and production.
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| 3. |
- Bahuguna, Jyotika, et al.
(författare)
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Existence and control of Go/No-Go decision transition threshold in the striatum
- 2015
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Ingår i: PloS Computational Biology. - : PLOS. - 1553-734X .- 1553-7358. ; 11:4
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Tidskriftsartikel (refereegranskat)abstract
- A typical Go/No-Go decision is suggested to be implemented in the brain via the activation of the direct or indirect pathway in the basal ganglia. Medium spiny neurons (MSNs) in the striatum, receiving input from cortex and projecting to the direct and indirect pathways express D1 and D2 type dopamine receptors, respectively. Recently, it has become clear that the two types of MSNs markedly differ in their mutual and recurrent connectivities as well as feedforward inhibition from FSIs. Therefore, to understand striatal function in action selection, it is of key importance to identify the role of the distinct connectivities within and between the two types of MSNs on the balance of their activity. Here, we used both a reduced firing rate model and numerical simulations of a spiking network model of the striatum to analyze the dynamic balance of spiking activities in D1 and D2 MSNs. We show that the asymmetric connectivity of the two types of MSNs renders the striatum into a threshold device, indicating the state of cortical input rates and correlations by the relative activity rates of D1 and D2 MSNs. Next, we describe how this striatal threshold can be effectively modulated by the activity of fast spiking interneurons, by the dopamine level, and by the activity of the GPe via pallidostriatal backprojections. We show that multiple mechanisms exist in the basal ganglia for biasing striatal output in favour of either the `Go' or the `No-Go' pathway. This new understanding of striatal network dynamics provides novel insights into the putative role of the striatum in various behavioral deficits in patients with Parkinson's disease, including increased reaction times, L-Dopa-induced dyskinesia, and deep brain stimulation-induced impulsivity.
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| 4. |
- 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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| 5. |
- Bahuguna, Jyotika
(författare)
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Structure-Dynamics relationship in basalganglia: Implications for brain function
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In this thesis, I have used a combination of computational models such as mean field and spikingnetwork simulations to study various sub-circuits of basal ganglia. I first studied the striatum(chapter 2), which is the input nucleus of basal ganglia. The two types of Medium SpinyNeurons (MSNs), D1 and D2-MSNs, together constitute 98% of the neurons in striatum. Thecomputational models so far have treated striatum as a homogenous unit and D1 and D2 MSNs asinterchangeable subpopulations. This implied that a bias in a Go/No-Go decision is enforced viaexternal agents to the striatum (eg. cortico-striatal weights), thereby assigning it a passive role.New data shows that there is an inherent asymmetry in striatal circuits. In this work, I showedthat striatum due to its asymmetric connectivity acts as a decision transition threshold devicefor the incoming cortical input. This has significant implications on the function of striatum asan active participant in influencing the bias towards a Go/No-Go decision. The striatal decisiontransition threshold also gives mechanistic explanations for phenomena such as L-Dopa InducedDyskinesia (LID), DBS-induced impulsivity, etc. In chapter 3, I extend the mean field model toinclude all the nuclei of basal ganglia to specifically study the role of two new subpopulationsfound in GPe (Globus Pallidus Externa). Recent work shows that GPe, also earlier consideredto be a homogenous nucleus, has at least two subpopulations which are dichotomous in theiractivity with respect to the cortical Slow Wave (SWA) and beta activity. Since the data for thesesubpopulations are missing, a parameter search was performed for effective connectivities usingGenetic Algorithms (GA) to fit the available experimental data. One major result of this studyis that there are various parameter combinations that meet the criteria and hence the presenceof functional homologs of the basal ganglia network for both pathological (PD) and healthynetworks is a possibility. Classifying all these homologous networks into clusters using somehigh level features of PD shows a large variance, hinting at the variance observed among the PDpatients as well as their response to the therapeutic measures. In chapter 4, I collaborated on aproject to model the role of STN and GPe burstiness for pathological beta oscillations as seenduring PD. During PD, the burstiness in the firing patterns of GPe and STN neurons are shownto increase. We found that in the baseline state, without any bursty neurons in GPe and STN,the GPe-STN network can transition to an oscillatory state through modulating the firing ratesof STN and GPe neurons. Whereas when GPe neurons are systematically replaced by burstyneurons, we found that increase in GPe burstiness enforces oscillations. An optimal % of burstyneurons in STN destroys oscillations in the GPe-STN network. Hence burstiness in STN mayserve as a compensatory mechanism to destroy oscillations. We also propose that bursting inGPe-STN could serve as a mechanism to initiate and kill oscillations on short time scales, asseen in the healthy state. The GPe-STN network however loses the ability to kill oscillations inthe pathological state.
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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, 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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| 9. |
- 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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| 10. |
- Bujan, Alejandro, et al.
(författare)
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Role of Input Correlations in Shaping the Variability and Noise Correlations of Evoked Activity in the Neocortex
- 2015
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Ingår i: Journal of Neuroscience. - 0270-6474 .- 1529-2401. ; 35:22, s. 8611-8625
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Tidskriftsartikel (refereegranskat)abstract
- Recent analysis of evoked activity recorded across different brain regions and tasks revealed a marked decrease in noise correlations and trial-by-trial variability. Given the importance of correlations and variability for information processing within the rate coding paradigm, several mechanisms have been proposed to explain the reduction in these quantities despite an increase in firing rates. These models suggest that anatomical clusters and/or tightly balanced excitation-inhibition can generate intrinsic network dynamics that may exhibit a reduction in noise correlations and trial-by-trial variability when perturbed by an external input. Such mechanisms based on the recurrent feedback crucially ignore the contribution of feedforward input to the statistics of the evoked activity. Therefore, we investigated how statistical properties of the feedforward input shape the statistics of the evoked activity. Specifically, we focused on the effect of input correlation structure on the noise correlations and trial-by-trial variability. We show that the ability of neurons to transfer the input firing rate, correlation, and variability to the output depends on the correlations within the presynaptic pool of a neuron, and that an input with even weak within-correlations can be sufficient to reduce noise correlations and trial-by-trial variability, without requiring any specific recurrent connectivity structure. In general, depending on the ongoing activity state, feedforward input could either increase or decrease noise correlation and trial-by-trial variability. Thus, we propose that evoked activity statistics are jointly determined by the feedforward and feedback inputs.
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