| 1. |
- Belic, Jovana, 1987-
(författare)
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Automatic detection of exudates in retinal images
- 2010
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Konferensbidrag (refereegranskat)abstract
- Nowadays, automatic detection of different diseases plays an important role in early and reliable diagnosis, which leads to faster recovery and significant reduction in health care costs. One such disease is diabetic retinopathy, which is induced by diabetes and is manifested through the gradual loss of eye blood vessels. Exudates are a form of diabetic retinopathy, and the idea of this paper was developing the program which would be used for automatic recognition of places that are potentially exudates in retinal images. The program was made in MatLab and three different methods were used. Also, a method for detection of blind spots was developed, concerning importance of it for appropriate detection of exudates.
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| 2. |
- Belic, Jovana, 1987-, et al.
(författare)
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Bayesian approach to handle missing limbs in Neuroprosthetics
- 2014
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Konferensbidrag (refereegranskat)abstract
- Motor synergies have been supposed to simplify motor control [1]-[5]. In order to test it, we exploit the correlations of our hand's joints to discover some underlying simplicity in a complex stream of behavioral actions. Instead of averaging variability out, we take the view that the structure of variability may contain valuable information about the task being performed. Therefore, we asked 7 subjects to interact in 17 daily-life situations and quantified behavior in principled manner using cyber glove technology. We combined Probabilistic Principal Component Analysis (PPCA) with a Bayesian classifier to analyze the data. Our key findings are: 1. we confirmed that hand control is low-dimensional, where 4-5 dimensions were sufficient to explain 80-90% of the variability in the movement data [6]. 2. We established a universally applicable measure of manipulative complexity that allowed us to measure this quantity across vastly different tasks. 3. We discovered that within the first 1000 ms of an action the hand shape already configures itself to vastly different tasks, enabling us to reliable predict the action intention [6]. 4. We suggest how using the statistics of natural finger movements paired with Bayesian latent variable model can be used to infer the movements of missing limbs from existing limbs to control e.g. a prosthetic device. Overall, these predictabilities could be used to build intelligent Neuroprosthetics for lost fingers that implement the task from the movement of the remaining limbs.ReferencesSantello, M., Flanders, M., Soechting, J.F. (1998). Postural hand synergies for tool use. J Neurosci. 18, 10105–10115.Todorov, E., Ghahramani, Z. (2004). Analysis of the synergies underlying complex hand manipulation. Conf Proc. IEEE Eng. Med. Biol. Soc. 6, 4637-4640.Weiss, E., Flanders, M. (2004). Muscular and Postural Synergies of the Human Hand. J. Neurophysiol. 92, 523-535.Tresch, M.C., Cheung, V.C.K., d’Avella, A. (2006). Matrix factorization algorithms for the identification of muscle synergies: evaluation on simulated and experimental data sets. J Neurophysiol. 95, 2199–2212.Faisal, A., Stout D., Apel, J., Bradley, B. (2010). The Manipulative Complexity of Lower Paleolithic Stone Toolmaking. PloS ONE 5(11): e13718.Belić, J.J., Faisal, A.A. (2011). The structured variability of finger motor coordination in daily tasks. BMC Neuroscience, doi:10.1186/1471-2202-12-S1-P102.
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| 3. |
- Belic, Jovana, 1987-, et al.
(författare)
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Behavior Discrimination Using a Discrete Wavelet Based Approach for Feature Extraction on Local Field Potentials in the Cortex and Striatum
- 2015
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Ingår i: 7th International IEEE/EMBS Conference on Neural Engineering (NER). - : IEEE conference proceedings. - 9781467363891 ; , s. 964-967
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Konferensbidrag (refereegranskat)abstract
- Linkage between behavioral states and neural activity is one of the most important challenges in neuroscience. The network activity patterns in the awake resting state and in the actively behaving state in rodents are not well understood, and a better tool for differentiating these states can provide insights on healthy brain functions and its alteration with disease. Therefore, we simultaneously recorded local field potentials (LFPs) bilaterally in motor cortex and striatum, and measured locomotion from healthy, freely behaving rats. Here we analyze spectral characteristics of the obtained signals and present an algorithm for automatic discrimination of the awake resting and the behavioral states. We used the Support Vector Machine (SVM) classifier and utilized features obtained by applying discrete wavelet transform (DWT) on LFPs, which arose as a solution with high accuracy.
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| 4. |
- Belic, Jovana, 1987-, et al.
(författare)
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Decoding of human hand actions to handle missing limbs in neuroprosthetics
- 2015
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Ingår i: Frontiers in Computational Neuroscience. - : Frontiers Research Foundation. - 1662-5188. ; 9:27, s. 1-11
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Tidskriftsartikel (refereegranskat)abstract
- The only way we can interact with the world is through movements, and our primary interactions are via the hands, thus any loss of hand function has immediate impact on our quality of life. However, to date it has not been systematically assessed how coordination in the hand's joints affects every day actions. This is important for two fundamental reasons. Firstly, to understand the representations and computations underlying motor control “in-the-wild” situations, and secondly to develop smarter controllers for prosthetic hands that have the same functionality as natural limbs. In this work we exploit the correlation structure of our hand and finger movements in daily-life. The novelty of our idea is that instead of averaging variability out, we take the view that the structure of variability may contain valuable information about the task being performed. We asked seven subjects to interact in 17 daily-life situations, and quantified behavior in a principled manner using CyberGlove body sensor networks that, after accurate calibration, track all major joints of the hand. Our key findings are: (1) We confirmed that hand control in daily-life tasks is very low-dimensional, with four to five dimensions being sufficient to explain 80–90% of the variability in the natural movement data. (2) We established a universally applicable measure of manipulative complexity that allowed us to measure and compare limb movements across tasks. We used Bayesian latent variable models to model the low-dimensional structure of finger joint angles in natural actions. (3) This allowed us to build a naïve classifier that within the first 1000 ms of action initiation (from a flat hand start configuration) predicted which of the 17 actions was going to be executed—enabling us to reliably predict the action intention from very short-time-scale initial data, further revealing the foreseeable nature of hand movements for control of neuroprosthetics and tele operation purposes. (4) Using the Expectation-Maximization algorithm on our latent variable model permitted us to reconstruct with high accuracy (<5–6° MAE) the movement trajectory of missing fingers by simply tracking the remaining fingers. Overall, our results suggest the hypothesis that specific hand actions are orchestrated by the brain in such a way that in the natural tasks of daily-life there is sufficient redundancy and predictability to be directly exploitable for neuroprosthetics.
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| 5. |
- Belic, Jovana, 1987-, et al.
(författare)
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Detecting and comparing the onset of self-paced and cue-based finger movements from EEG signals
- 2015
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Ingår i: 7th Annual International IEEE Conference on Computer Science and Electronic Engineering (CEEC). - Colchester, UK : IEEE conference proceedings. ; , s. 157-160
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Konferensbidrag (refereegranskat)abstract
- We asked four subjects to perform the task of pressing a taster button with their thumbs, while their EEG recordings were obtained, in order to determine the probability of the subjects' intention to make the movement in comparison to the idle state. Humans usually spontaneously decide when to initiate movements to complete daily-life tasks, but sometimes our movements can also be externally triggered. Thus, the subjects first performed motor tasks at the instants defined by the animation shown on the screen and second, the subjects performed self-initiated movements. In this paper, we study if there is a difference in the classification results and coherence measures of EEG signals in these two paradigms. We used the Support Vector Machine (SVM) classifier on features extracted by applying Burg's algorithm to EEG signals, which arose as a solution with high accuracy.
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| 6. |
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| 7. |
- 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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| 8. |
- 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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| 9. |
- Belic, Jovana, 1987-, et al.
(författare)
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Mapping of Cortical Avalanches to the Striatum
- 2015. - 4
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Ingår i: Advances in Cognitive Neurodynamics. - Dordrecht : Springer Netherlands. - 9789401795470 ; , s. 291-297
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Bokkapitel (refereegranskat)abstract
- Neuronal avalanches are found in the resting state activity of the mammaliancortex. Here we studied whether and how cortical avalanches are mappedonto the striatal circuitry, the first stage of the basal ganglia. We first demonstrate using organotypic cortex-striatum-substantia nigra cultures from rat that indeed striatal neurons respond to cortical avalanches originating in superficial layers. We simultaneously recorded spontaneous local field potentials (LFPs) in the cortical and striatal tissue using high-density microelectrode arrays. In the cortex, spontaneous neuronal avalanches were characterized by intermittent spatiotemporal activity clusters with a cluster size distribution that followed a power law with exponent 1.5. In the striatum, intermittent spatiotemporal activity was found to correlate with cortical avalanches. However, striatal negative LFP peaks (nLFPs) did not showavalanche signatures, but formed a cluster size distribution that had a much steeper drop-off, i.e., lacked large spatial clusters that are commonly expected for avalanche dynamics. The underlying de-correlation of striatal activity could have its origin in the striatum through local inhibition and/or could result from a particular mapping in the corticostriatal pathway. Here we show, using modeling, that highly convergent corticostriatal projections can map spatially extended cortical activity into spatially restricted striatal regimes.
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| 10. |
- 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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