| 1. |
- Löfhede, Johan, 1978, et al.
(author)
-
Automatic classification of background EEG activity in healthy and sick neonates
- 2010
-
In: Journal of Neural Engineering. - : IOP Publishing. - 1741-2560 .- 1741-2552. ; 7:1
-
Journal article (peer-reviewed)abstract
- The overall aim of our research is to develop methods for a monitoring system to be used at neonatal intensive care units. When monitoring a baby, a range of different types of background activity needs to be considered. In this work, we have developed a scheme for automatic classification of background EEG activity in newborn babies. EEG from six full-term babies who were displaying a burst suppression pattern while suffering from the after-effects of asphyxia during birth was included along with EEG from 20 full-term healthy newborn babies. The signals from the healthy babies were divided into four behavioural states: active awake, quiet awake, active sleep and quiet sleep. By using a number of features extracted from the EEG together with Fisher’s linear discriminant classifier we have managed to achieve 100% correct classification when separating burst suppression EEG from all four healthy EEG types and 93% true positive classification when separating quiet sleep from the other types. The other three sleep stages could not be classified. When the pathological burst suppression pattern was detected, the analysis was taken one step further and the signal was segmented into burst and suppression, allowing clinically relevant parameters such as suppression length and burst suppression ratio to be calculated. The segmentation of the burst suppression EEG works well, with a probability of error around 4%.
|
|
| 2. |
- Mohlin, Camilla, 1972-, et al.
(author)
-
Further assessment of neuropathology in retinal explants and neuroprotection by human neural progenitor cells
- 2011
-
In: Journal of Neural Engineering. - : IOP Publishing. - 1741-2560 .- 1741-2552. ; 8:6, s. 066012-
-
Journal article (peer-reviewed)abstract
- Explanted rat retinas show progressive photoreceptor degeneration that appears to be caspase-12-dependent. Decrease in photoreceptor density eventually affects the inner retina, particularly in the bipolar cell population. Explantation and the induced photoreceptor degeneration are accompanied by activation of Muller and microglia cells. The goal of this study was to determine whether the presence of a feeder layer of human neural progenitor cells (hNPCs) could suppress the degenerative and reactive changes in the explants. Immunohistochemical analyses showed considerable sprouting of rod photoreceptor axon terminals into the inner retina and reduced densities of cone and rod bipolar cells. Both sprouting and bipolar cell degenerations were significantly lower in retinas cultured with feeder layer cells compared to cultured controls. A tendency toward reduced microglia activation in the retinal layers was also noted in the presence of feeder layer cells. These results indicate that hNPCs or factors produced by them can limit the loss of photoreceptors and secondary injuries in the inner retina. The latter may be a consequence of disrupted synaptic arrangement.
|
|
| 3. |
- Lind, Gustav, et al.
(author)
-
Gelatine-embedded electrodes-a novel biocompatible vehicle allowing implantation of highly flexible microelectrodes.
- 2010
-
In: Journal of Neural Engineering. - : IOP Publishing. - 1741-2560 .- 1741-2552. ; 7:4
-
Journal article (peer-reviewed)abstract
- Chronic neural interfaces that are both structurally and functionally stable inside the brain over years or decades hold great promise to become an invaluable clinical tool in the near future. A key flaw in the current electrode interfaces is that their recording capabilities deteriorate over time, possibly due to the lack of flexibility, which causes movements in relation to the neural tissue that result in small inflammations and loss of electrode function. We have developed a new neural probe using the stabilizing property of gelatine that allows the implantation of ultra-thin and flexible electrodes into the central nervous system. The microglial and astrocytic reactions evoked by implanted gelatine needles, as well as the wire bundles in combination with gelatine, were investigated using immunohistochemistry and fluorescence microscopy up to 12 weeks after implantation. The results indicate that pure gelatine needles were stiff enough to penetrate the brain tissue on their own, and evoked a significantly smaller chronic scar than stab wounds. Moreover, gelatine embedding appeared to reduce the acute reactions caused by the implants and we found no adverse effects of gelatine or gelatine-embedded electrodes. Successful electrophysiological recordings were made from very thin electrodes implanted in this fashion.
|
|
| 4. |
- Thorbergsson, Palmi Thor, et al.
(author)
-
Minimizing data transfer with sustained performance in wireless brain–machine interfaces
- 2012
-
In: Journal of Neural Engineering. - : IOP Publishing. - 1741-2560 .- 1741-2552. ; 9:3
-
Journal article (peer-reviewed)abstract
- Brain–machine interfaces (BMIs) may be used to investigate neural mechanisms or to treat the symptoms of neurological disease and are hence powerful tools in research and clinical practice. Wireless BMIs add flexibility to both types of applications by reducing movement restrictions and risks associated with transcutaneous leads. However, since wireless implementations are typically limited in terms of transmission capacity and energy resources, the major challenge faced by their designers is to combine high performance with adaptations to limited resources. Here, we have identified three key steps in dealing with this challenge: (1) the purpose of the BMI should be clearly specified with regard to the type of information to be processed; (2) the amount of raw input data needed to fulfill the purpose should be determined, in order to avoid over- or under-dimensioning of the design; and (3) processing tasks should be allocated among the system parts such that all of them are utilized optimally with respect to computational power, wireless link capacity and raw input data requirements. We have focused on step (2) under the assumption that the purpose of the BMI (step 1) is to assess single- or multi-unit neuronal activity in the central nervous system with single-channel extracellular recordings. The reliability of this assessment depends on performance in detection and sorting of spikes. We have therefore performed absolute threshold spike detection and spike sorting with the principal component analysis and fuzzy c-means on a set of synthetic extracellular recordings, while varying the sampling rate and resolution, noise level and number of target units, and used the known ground truth to quantitatively estimate the performance. From the calculated performance curves, we have identified the sampling rate and resolution breakpoints, beyond which performance is not expected to increase by more than 1–5%. We have then estimated the performance of alternative algorithms for spike detection and spike sorting in order to examine the generalizability of our results to other algorithms. Our findings indicate that the minimization of recording noise is the primary factor to consider in the design process. In most cases, there are breakpoints for sampling rates and resolution that provide guidelines for BMI designers in terms of minimum amount raw input data that guarantees sustained performance. Such guidelines are essential during system dimensioning. Based on these findings we conclude by presenting a quantitative task-allocation scheme that can be followed to achieve optimal utilization of available resources.
|
|
| 5. |
- Pham, Tuan D., et al.
(author)
-
The hidden-Markov brain comparison and inference of white matter hyperintensities on magnetic resonance imaging (MRI)
- 2011
-
In: Journal of Neural Engineering. - : IOP Publishing. - 1741-2560 .- 1741-2552. ; 8:1, s. 1-10
-
Journal article (peer-reviewed)abstract
- Rating and quantification of cerebral white matter hyperintensities on magnetic resonance imaging (MRI) are important tasks in various clinical and scientific settings. As manual evaluation is time consuming and imprecise, much effort has been made to automate the quantification of white matter hyperintensities. There is rarely any report that attempts to study the similarity/dissimilarity of white matter hyperintensity patterns that have different sizes, shapes and spatial localizations on the MRI. This paper proposes an original computational neuroscience framework for such a conceptual study with a standpoint that the prior knowledge about white matter hyperintensities can be accumulated and utilized to enable a reliable inference of the rating of a new white matter hyperintensity observation. This computational approach for rating inference of white matter hyperintensities, which appears to be the first study, can be utilized as a computerized rating-assisting tool and can be very economical for diagnostic evaluation of brain tissue lesions.
|
|
