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Permanent URI for this communityhttps://hdl.handle.net/20.500.14288/2
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Publication Metadata only Detection of stride time and stance phase ratio from accelerometer data for gait analysis(Institute of Electrical and Electronics Engineers Inc., 2022) N/A; Department of Computer Engineering; N/A; Department of Computer Engineering; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Vural, Atay; Erzin, Engin; Akar, Kardelen; Tokmak, Fadime; Köprücü, Nursena; Emirdağı, Ahmet Rasim; Faculty Member; Faculty Member; Master Student; Student; Student; Student; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); N/A; N/A; N/A; N/A; N/A; School of Medicine; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; College of Engineering; 182369; 34503; N/A; N/A; N/A; N/AStride time and stance phase ratio are supportive biomarkers used in the diagnosis and treatment of gait disorders and are currently frequently used in research studies. In this study, the 3-axis accelerometer signal, taken from the foot, was denoised by a low-pass FIR (finite impulse response) filter. By using the fundamental frequency analysis the dominant frequency was found and with that frequency an optimal length for a window to be shifted across the whole signal for further purposes. And the turning region was extracted by using the Pearson correlation coefficient with the segments that overlapped by shifting the selected window over the whole signal, after getting the walking segments the stride time parameter is calculated by using a simple peak-picking algorithm. The stance and swing periods of the pseudo-steps, which emerged as a result of the double step time calculation algorithm, were found with the dynamic time warping method, and the ratio of the stance phase in a step to the whole step was calculated as a percentage. The results found were compared with the results of the APDM system, and the mean absolute error rate was calculated as 0.029 s for the stride time and 0.0084 for the stance phase ratio.Publication Open Access Nanoengineering InP quantum dot-based photoactive biointerfaces for optical control of neurons(Frontiers, 2021) Ulgut, Burak; Department of Electrical and Electronics Engineering; Department of Chemical and Biological Engineering; N/A; Department of Electrical and Electronics Engineering; Department of Chemical and Biological Engineering; Nizamoğlu, Sedat; Kavaklı, İbrahim Halil; Şahin, Afsun; Karatüm, Onuralp; Aria, Mohammad Mohammadi; Eren, Güncem Özgün; Yıldız, Erdost; Melikov, Rustamzhon; Srivastava, Shashi Bhushan; Sürme, Saliha; Doğru-Yüksel, Itır Bakış; Jalali, Houman Bahmani; Faculty Member; Faculty Member; Faculty Member; PhD Student; Researcher; Teaching Faculty; PhD Student; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of Engineering; School of Medicine; Graduate School of Sciences and Engineering; Graduate School of Health Sciences; 130295; 40319; 171267; N/A; N/A; N/A; N/A; N/A; N/A; N/A; N/A; N/ALight-activated biointerfaces provide a non-genetic route for effective control of neural activity. InP quantum dots (QDs) have a high potential for such biomedical applications due to their uniquely tunable electronic properties, photostability, toxic-heavy-metal-free content, heterostructuring, and solution-processing ability. However, the effect of QD nanostructure and biointerface architecture on the photoelectrical cellular interfacing remained unexplored. Here, we unravel the control of the photoelectrical response of InP QD-based biointerfaces via nanoengineering from QD to device-level. At QD level, thin ZnS shell growth (similar to 0.65 nm) enhances the current level of biointerfaces over an order of magnitude with respect to only InP core QDs. At device-level, band alignment engineering allows for the bidirectional photoelectrochemical current generation, which enables light-induced temporally precise and rapidly reversible action potential generation and hyperpolarization on primary hippocampal neurons. Our findings show that nanoengineering QD-based biointerfaces hold great promise for next-generation neurostimulation devices.Item Metadata only Physical mechanisms of emerging neuromodulation modalities(IOP Publishing Ltd, 2023) 0000-0002-7669-9589; 0000-0002-3543-5894; 0000-0002-6209-6912; 0000-0002-7534-9392; 0000-0003-0394-5790; N/A; N/A; N/A; N/A; Department of Electrical and Electronics Engineering; Karatüm, Onuralp; Han, Mertcan; Erdoğan, Ezgi Tuna; Karamürsel, Sacit; Nizamoğlu, Sedat; PhD Student; Master Student; Faculty Member; Faculty Member; Faculty Member; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; School of Medicine; School of Medicine; College of Engineering; N/A; N/A; 168716; 19597; 130295One of the ultimate goals of neurostimulation field is to design materials, devices and systems that can simultaneously achieve safe, effective and tether-free operation. For that, understanding the working mechanisms and potential applicability of neurostimulation techniques is important to develop noninvasive, enhanced, and multi-modal control of neural activity. Here, we review direct and transduction-based neurostimulation techniques by discussing their interaction mechanisms with neurons via electrical, mechanical, and thermal means. We show how each technique targets modulation of specific ion channels (e.g. voltage-gated, mechanosensitive, heat-sensitive) by exploiting fundamental wave properties (e.g. interference) or engineering nanomaterial-based systems for efficient energy transduction. Overall, our review provides a detailed mechanistic understanding of neurostimulation techniques together with their applications to in vitro, in vivo, and translational studies to guide the researchers toward developing more advanced systems in terms of noninvasiveness, spatiotemporal resolution, and clinical applicability.Publication Metadata only Spike timing precision of neuronal circuits(Springer, 2018) N/A; N/A; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Kılınç, Deniz; Demir, Alper; PhD Student; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; N/A; 3756Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.Publication Metadata only Three-dimensional neuron-astrocyte construction on matrigel enhances establishment of functional voltage-gated sodium channels(Wiley-Blackwell, 2021) N/A; N/A; N/A; N/A; Department of Electrical and Electronics Engineering; N/A; N/A; Department of Electrical and Electronics Engineering; Karahüseyinoğlu, Serçin; Şekerdağ, Emine; Aria, Mohammad Mohammadi; Taş, Yağmur Çetin; Nizamoğlu, Sedat; Solaroğlu, İhsan; Özdemir, Yasemin Gürsoy; Faculty Member; Researcher; PhD Student; Researcher; Faculty Member; Faculty Member; Faculty Member; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); School of Medicine; N/A; Graduate School of Sciences and Engineering; N/A; College of Engineering; School of Medicine; N/A; 110772; N/A; N/A; N/A; 130295; 102059; 170592This study aimed to investigate and compare cell growth manners and functional differences of primary cortical neurons cultured on either poly-d-lysine (PDL) and or Matrigel, to delineate the role of extracellular matrix on providing resemblance to in vivo cellular interactions in nervous tissue. Primary cortical neurons, obtained from embryonic day 15 mice pups, seeded either on PDL- or Matrigel-coated culture ware were investigated by DIC/bright field and fluorescence/confocal microscopy for their morphology, 2D and 3D structure, and distribution patterns. Patch clamp, western blot, and RT-PCR studies were performed to investigate neuronal firing thresholds and sodium channel subtypes Nav1.2 and Nav1.6 expression. Cortical neurons cultured on PDL coating possessed a 2D structure composed of a few numbers of branched and tortuous neurites that contacted with each other in one to one manner, however, neurons on Matrigel coating showed a more complicated dimensional network that depicted tight, linear axonal bundles forming a 3D interacted neuron-astrocyte construction. This difference in growth patterns also showed a significant alteration in neuronal firing threshold which was recorded between 80 < linj > 120 pA on PDL and 2 < linj > 160 pA on Matrigel. Neurons grown up on Matrigel showed increased levels of sodium channel protein expression of Nav1.2 and Nav1.6 compared to neurons on PDL. These results have demonstrated that a 3D interacted neuron-astrocyte construction on Matrigel enhances the development of Nav1.2 and Nav1.6 in vitro and decreases neuronal firing threshold by 40 times compared to conventional PDL, resembling in vivo neuronal networks and hence would be a better in vitro model of adult neurons.