Gaute Einevoll, Ph.D.
Professor of Physics, Department of Mathematical Sciences & Technology, Norwegian University of Life Sciences (UMB)
Multiscale modeling of cortical network activity: Key challenges
Gaute T. Einevoll Computational Neuroscience Group, Norwegian University of Life Sciences, 1432 Ås, Norway; Norwegian National Node of the International Neuroinformatics Coordinating Facility (INCF)
Several challenges must be met in the development of multiscale models of cortical network activity. In the presentation I will, based on ongoing work in our group (http://compneuro.umb.no/ ) on multiscale modeling of cortical columns, outline some of them. In particular,
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Combined modeling schemes for neuronal, glial and vascular dynamics [1,2],
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Development of sets of interconnected models describing system at different levels of biophysical detail [3-5],
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Multimodal modeling, i.e., how to model what you can measure [6-12],
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How to model when you don’t know all the parameters, and
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Development of neuroinformatics tools and routines to do simulations efficiently and accurately [13,14].
References:
- L. Øyehaug, I. Østby, C. Lloyd, S.W. Omholt, and G.T. Einevoll: Dependence of spontaneous neuronal firing and depolarisation block on astroglial membrane transport mechanisms, J Comput Neurosci 32, 147-165 (2012)
- I. Østby, L. Øyehaug, G.T. Einevoll, E. Nagelhus, E. Plahte, T. Zeuthen, C. Lloyd, O.P. Ottersen, and S.W. Omholt: Astrocytic mechanisms explaining neural-activity-induced shrinkage of extraneuronal space, PLoS Comp Biol 5, e1000272 (2009)
- T. Heiberg, B. Kriener, T. Tetzlaff, A. Casti, G.T. Einevoll, and H.E. Plesser: Firing-rate models can describe the dynamics of the retina-LGN connection, J Comput Neurosci (2013)
- T. Tetzlaff, M. Helias, G.T. Einevoll, and M. Diesmann: Decorrelation of neural-network activity by inhibitory feedback, PLoS Comp Biol 8, e10002596 (2012).
- E. Nordlie, T. Tetzlaff, and G.T. Einevoll: Rate dynamics of leaky integrate-and-fire neurons with strong synapses, Frontiers in Comput Neurosci 4, 149 (2010)
- G.T. Einevoll, F. Franke, E. Hagen, C. Pouzat, K.D. Harris: Towards reliable spike-train recording from thousands of neurons with multielectrodes, Current Opinion in Neurobiology 22, 11-17 (2012)
- H. Linden, T Tetzlaff, TC Potjans, KH Pettersen, S Grun, M Diesmann, GT Einevoll: Modeling the spatial reach of LFP, Neuron 72, 859-872 (2011).
- H. Linden, K.H. Pettersen, and G.T. Einevoll: Intrinsic dendritic filtering gives low-pass power spectra of local field potentials, J Computational Neurosci 29, 423-444 (2010)
- K.H. Pettersen and G.T. Einevoll: Amplitude variability and extracellular low-pass filtering of neuronal spikes, Biophysical Journal 94, 784-802 (2008).
- K.H. Pettersen, E. Hagen, and G.T. Einevoll: Estimation of population firing rates and current source densities from laminar electrode recordings, J Comput Neurosci 24, 291-313 (2008).
- K. Pettersen, A. Devor, I. Ulbert, A.M. Dale and G.T. Einevoll. Current-source density estimation based on inversion of electrostatic forward solution: Effects of finite extent of neuronal activity and conductivity discontinuities, Journal of Neuroscience Methods 154, 116-133 (2006).
- G.T. Einevoll, K. Pettersen, A. Devor, I. Ulbert, E. Halgren and A.M. Dale: Laminar Population Analysis: Estimating firing rates and evoked synaptic activity from multielectrode recordings in rat barrel cortex, Journal of Neurophysiology 97, 2174-2190 (2007).
- LFPy: A tool for simulation of extracellular potentials (http://compneuro.umb.no)
- E. Nordlie, M.-O. Gewaltig, H. E. Plesser: Towards reproducible descriptions of neuronal network models, PLoS Comp Biol 5, e1000456 (2009).
Hideaki Nagase, Ph.D.
Kennedy Institute of Rheumatology-Centre for Degenerative Diseases, University of Oxford, UK
Osteoarthritis: diagnosis, treatment and challenges
Hideaki Nagase1, Ngee Han Lim1, George Bou-Gharios1, Ernst Meinjohanns2 and Morten Meldal3
- Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, London, W6 8LH UK
- Carlsberg Laboratory, Copenhagen, Denmark,
- Nano-Science Center, Department of Chemistry, University of Copenhagen, Denmark
Osteoarthritis (OA) is the most prevalent age-related degenerative joint disease. With the expanding ageing population, it imposes a major socio-economic burden on society. A key feature of OA is a gradual loss of articular cartilage and deformation of bone, resulting in the impairment of joint function. Currently, there is no effective disease-modifying treatment except joint replacement surgery. There are many possible causes of cartilage loss (e.g. mechanical load, injury, reactive oxygen species, aging, etc.) and etiological factors (obesity, genetics), but the degradation of cartilage is primarily caused by elevated levels of active metalloproteinases. It is therefore attractive to consider proteinase inhibitors as potential therapeutics. However, there are several hurdles to overcome, namely early diagnosis and continuous monitoring of the efficacy of inhibitor therapeutics. We are therefore aiming at developing non-invasive probes to detect cartilage degrading metalloproteinase activities.
We have designed in vivo imaging probes to detect MMP-13 (collagenase 3) activity that participates in OA by degrade cartilage collagen II and MMP-12 (macrophage elastase) activity involved in inflammatory arthritis. These activity-based probes consist of a peptide that is selectively cleaved by the target proteinase, a near-infrared fluorophore and a quencher. The probe’s signal multiplies upon proteolysis. They were first used to follow the respective enzyme activity in vivo in the mouse model of collagen-induced arthritis and we found MMP-12 activity probe (MMP12AP) activation peaked at 5 days after onset of the disease, whereas MMP13AP activation was observed at 10-15 days. The in vivo activation of these probes was inhibited by specific low molecule inhibitors. We proceeded to test both probes in the mouse model of OA induced by the surgical destabilization of medial meniscus of the knee joints. In this model, degradation of knee cartilage is first detected histologically 6 weeks after surgery with significant erosion detectable at 8 weeks. Little activation of MMP12AP was detected, which was expected, as macrophage migration is not obvious in OA. MMP13AP, on the other hand, was significantly activated in the operated knee at 6 weeks compared with the non-operated contralateral knee, but there were no significant differences between the operated and sham-operated knees. At 8 weeks, however, the signals in the operated knees were significantly higher than both the contralateral and sham-operated controls. Activation of aggrecanases and MMP-13 are observed before structural changes of cartilage. We are therefore currently improving the MMP-13 probe for earlier detection by attaching it to polymers that are retained in cartilage.
Leland H. Hartwell Ph.D.
2001 Nobel Laureate, Physiology & Medicine
Dr. Lee Hartwell received the 2001 Nobel Prize in Physiology / Medicine for his discovery of protein molecules that control the division of cells. He was the President and Director of the Fred Hutchinson Cancer Research Center in Seattle, Washington before moving to Arizona State University’s Center for Sustainable Health.
Dr. Hartwell is also adjunct faculty at Amrita University. He spoke to the delegates at Bioquest from his office in the US, over Amrita’s e-learning platform A-View. Given below are excerpts from his address.
I would like to address the young people in the audience. I know that many of you may have come to this meeting wondering, “How can I become a successful scientist? How can I prepare myself to make a contribution in this world?”
These questions are interesting to me also.
Believe it or not, I am still trying to be a successful scientist. That may surprise you since you probably think that a Nobel laureate must have found the answers. But the problem is that the answers to these questions change with time and the answers are different today than what they were when I began my career fifty years ago. The strategy of the 1960’s doesn’t work so well anymore. What is different now?
First, what we know now is much more. For example, by 1970, no genes from any organisms were sequenced. In 2013, we have the complete sequence of the human genome. Second, not only do we know much more today, accessing that knowledge is easy. Third, obtaining new information is much faster today.
Our rich understanding of science and technology is now needed to solve many serious problems. The human population has reached the size where we are utilizing all available resource of the planet. We are utilizing all of the agricultural land, all of the water, all of the forest and fishing resources. We are also polluting the planet that we live on.
We are polluting the land with fertilizers and pesticides; the oceans with acids and the atmosphere with carbon dioxide. We are using up top soil and ground water, thereby reducing our capacity to feed ourselves. We are using up petroleum, the energy source that our entire economy is dependent on. These are problems we were largely unaware of, fifty years ago. But these are problems that must be solved in your life times.
The big question facing your generation is, how can human beings live sustainably on planet earth. Your two broad goals on sustainability are 1) leave the planet as you first found it for your future generations; don’t use up the resources and don’t pollute the planet 2) everyone deserves to have an equal share of the earth’s resources.
Income strongly determines one’s opportunities in life. Many poor people succumb to chronic diseases and unhealthy environments. This inequality undermines our ability to live sustainably. We can’t ask the poor to leave the planet as they found it if they can’t support their families. Education, healthcare, employment are essential to having a sustainable society.
How can we be a successful scientist in 2013?
1. First choose a problem to solve
2. Ask questions to understand why it is not solved
3. Collaborate with those who can help
4. Develop a solution that works in the real worldChronic diseases are our major burden and this burden will get worse. Heart disease, diabetes, cancer, dementia and other diseases. The good news is that the chronic diseases are largely preventable and more easily curable if detected early. One question that attracts me is how can we detect disease earlier when it can be more easily cured?
Can we use our increasing knowledge in molecular biology to identify biomarkers for early disease detection?
We need to collaborate very closely with clinicians who care for patients to find out exactly where they need help.
I think if we apply our technology to important clinical questions we will actually save medical expenditure and be well on our way to making a great contribution to society.
Nader Pourmand, Ph.D.
Director, UCSC Genome Technology Center,University of California, Santa Cruz
Biosensor and Single Cell Manipulation using Nanopipettes
Approaching sub-cellular biological problems from an engineering perspective begs for the incorporation of electronic readouts. With their high sensitivity and low invasiveness, nanotechnology-based tools hold great promise for biochemical sensing and single-cell manipulation. During my talk I will discuss the incorporation of electrical measurements into nanopipette technology and present results showing the rapid and reversible response of these subcellular sensors to different analytes such as antigens, ions and carbohydrates. In addition, I will present the development of a single-cell manipulation platform that uses a nanopipette in a scanning ion-conductive microscopy technique. We use this newly developed technology to position the nanopipette with nanoscale precision, and to inject and/or aspirate a minute amount of material to and from individual cells or organelle without comprising cell viability. Furthermore, if time permits, I will show our strategy for a new, single-cell DNA/ RNA sequencing technology that will potentially use nanopipette technology to analyze the minute amount of aspirated cellular material.
Michelle Hermiston, MD, Ph.D.
Assistant Professor, Department of Pediatrics University of California San Francisco, USA
Interrogating Signaling Networks at the Single Cell Level In Primary Human Patient Samples
Multiparameter phosphoflow cytometry is a highly sensitive proteomic approach that enables monitoring of biochemical perturbations at the single cell level. By combining antisera to cell surface markers and key intracellular proteins, perturbations in signaling networks, cell survival and apoptosis mediators, cell cycle regulators, and/or modulators of other cellular processes can be analyzed in a highly reproducible and sensitive manner in the basal state and in response to stimulation or drug treatment. Advantages of this approach include the ability to identify the biochemical consequences of genetic and/or epigenetic changes in small numbers of cells, to map potential interplay between various signaling networks simultaneously in a single cell, and to interrogate potential mechanisms of drug resistance or response in a primary patient sample. Application of this technology to patients with acute lymphoblastic leukemia or the autoimmune disease systemic lupus erythematosus (SLE) will be discussed.
Karmeshu, Ph.D.
Dean & Professor, School of Computer & Systems Sciences & School of Computational & Integrative Sciences, Jawaharlal Nehru University, India.
Interspike Interval Distribution of Neuronal Model with distributed delay: Emergence of unimodal, bimodal and Power law
The study of interspike interval distribution of spiking neurons is a key issue in the field of computational neuroscience. A wide range of spiking patterns display unimodal, bimodal ISI patterns including power law behavior. A challenging problem is to understand the biophysical mechanism which can generate the empirically observed patterns. A neuronal model with distributed delay (NMDD) is proposed and is formulated as an integro-stochastic differential equation which corresponds to a non-markovian process. The widely studied IF and LIF models become special cases of this model. The NMDD brings out some interesting features when excitatory rates are close to inhibitory rates rendering the drift close to zero. It is interesting that NMDD model with gamma type memory kernel can also account for bimodal ISI pattern. The mean delay of the memory kernels plays a significant role in bringing out the transition from unimodal to bimodal ISI distribution. It is interesting to note that when a collection of neurons group together and fire together, the ISI distribution exhibits power law.
![Delegate Talk: Pt-Pd decorated TiO2 nanotube array for the non-enzymatic determination of glucose in neutral medium @ Amriteshwari Hall | Vallikavu | Kerala | India](http://www.amritabioquest.org/conference/2013/wp-content/uploads/sites/2/2015/02/biomed.jpg)
John Stanley, Satheesh Babu, Ramacahandran T and Bipin Nair
Pt-Pd decorated TiO2 nanotube array for the non-enzymatic determination of glucose in neutral medium
Rapidly expanding diabetic population and the complications associated with elevated glycemic levels necessitates the need for a highly sensitive, selective and stable blood glucose measurement strategy. The high sensitivity and selectivity of enzymatic sensors together with viable manufacturing technologies such as screen-printing have made a great social and economic impact. However, the intrinsic nature of the enzymes leads to lack of stability and consequently reduces shelf life and imposes the need for stringent storage conditions. As a result much effort has been directed towards the development of ‘enzyme-free’ glucose sensors (Park et al. 2006). In this paper, a non-enzymatic amperometric sensor for selective and sensitive direct electrooxidation of glucose in neutral medium was fabricated based on Platinum-Palladium (Pt–Pd) nanoparticle decorated titanium dioxide (TiO2) nanotube arrays. Highly ordered TiO2 nanotube arrays were obtained using a single step anodization process (Grimes C A and Mor G K 2009) over which Pt–Pd nanoparticles where electrochemically deposited. Scanning Electron Microscopy (SEM) analysis revealed the diameter of the TiO2 nanotubes to be approximately 40 nm. Elemental analysis after electrochemical deposition confirms the presence of Pt–Pd. Electrochemical characterization of the sensor was carried out using cyclic voltammetry technique (−1.0 to +1.0V) in phosphate buffer saline (PBS) pH 7.4. All further glucose oxidation studies were performed in PBS (pH 7.4). The sensor exhibited good linear response towards glucose for a concentration range of 1 μM to 20mM with a linear regression coefficient of R = 0.998. The electrodes are found to be selective in the presence of other commonly interfering molecules such as ascorbic acid, uric acid, dopamine and acetamidophenol. Thus a nonenzymatic sensor with good selectivity and sensitivity towards glucose in neutral medium has been developed.