nonlinear differential equation model  (BioMimetic Therapeutics)

Journal: CPT: Pharmacometrics & Systems Pharmacology

Article Title: NONMEM Tutorial Part I: Description of Commands and Options, With Simple Examples of Population Analysis

doi: 10.1002/psp4.12404

Figure Lengend Snippet: List of built‐in models as of NONMEM 7.4 (PREDPP guide VI 1 )

Article Snippet: ADVAN9 , GENERAL NONLINEAR MODEL: LSODI ODE SOLVER, AND DIFFERENTIAL‐ALGEBRAIC EQUATIONS (ADE) , TRANS1 , , General nonlinear model with equilibrium compartments (ordinary and algebraic differential equations, LSODI1).

Techniques:

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: A cross section of the glabrous skin which shows individual type of mechanoreceptors. The obtained spike trains in response to a specific stimulus are also shown.

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques:

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: Parameter values of spiking model of SA-I and FA-I mechanoreceptors used in the simulations.

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques:

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: Scheduling diagram for spiking part of the (A) Merkel cell (SA-I), (B) Meissner's Corpuscle (FA-I). Membrane potential (v dynamic) and the membrane recovery variable (u dynamic).

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques: Membrane

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: The time response of the Merkel Cells (SA-I) mechanoreceptor in mV. (A) Spiking and (B) bursting response. In these simulations, the first panels show the input signal, the second panels display the MATLAB simulation of the spiking mechanoreceptor model and the third panels illustrate the VIVADO simulation of the proposed digital circuit.

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques:

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: The time response of the Meissner's Corpuscle (FA-I) mechanoreceptor in mV. (A) Spiking and (B) bursting responses. In these simulations, the first panels show the input signal, the second panels display the MATLAB simulation of the spiking mechanoreceptor model and the third panels illustrate the VIVADO simulation of the proposed digital circuit.

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques:

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: The timing of firing (A) the SA-I mechanoreceptor, (B) the FA-I mechanoreceptor for spiking/bursting responses obtained by the MATLAB simulations of the SA-I and FA-I mechanoreceptor models and VIVADO simulation of the proposed SA-I and FA-I digital mechanoreceptors. This figure corresponds to Figures , .

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques:

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: The phase plane of (A) the SA-I mechanoreceptor, (B) the FA-I mechanoreceptor for spiking responses. In each part, first panel shows the mechanoreceptor model simulated in MATLAB and the second panel displays the mechanoreceptor digital circuit simulated in VIVADO. This figure corresponds to Figures , , for spiking mode. It can be seen that the proposed circuit preserves the model dynamics.

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques:

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: The phase plane of (A) the SA-I mechanoreceptor, (B) the FA-I mechanoreceptor for bursting response. In each part, first panel shows the mechanoreceptor model simulated in MATLAB and the second panel displays the mechanoreceptor digital circuit simulated in VIVADO. This figure corresponds to Figures , , for bursting mode. It can be seen that the proposed circuit preserves the model dynamics.

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques:

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: The diagram for hardware testing of the mechanoreceptor digital circuit. In this case, the digital mechanoreceptor is implemented on the ZedBoard and the obtained signals after converting to analog signal will be displayed on oscilloscope. A 10-bit ADC was used for analog to digital conversion. However, a 16-bit DAC was used to convert the digital outputs of the ZedBoard to analog signals to be shown on the Oscilloscope.

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques:

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: The model for Merkel Cells (SA-I) and Meissner's Corpuscle (FA-I) mechanoreceptor. The FA-I receptor responds with action potentials during stimulus onset and offset. The SA-I receptor is active throughout the period of stimulus contact. The Izhikevich model was used for producing spiking/bursting responses.

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques:

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: The spiking response of the digital SA-I mechanoreceptor (yellow color) executed on the ZedBoard. Signals are physically produced and observed on the oscilloscope. The SA-I mechanoreceptor remains active during the period of stimulus contact. The filtered input of the A/D is shown in blue. The volt division for the output (input) channel was set on 500 mV (100mV).

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques: Produced

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: The bursting response of the digital SA-I mechanoreceptor (yellow color) executed on the ZedBoard. Signals are physically produced and observed on the oscilloscope. The filtered input of the A/D is shown in blue. The volt division for the output (input) channel was set on 500 mV (100mV).

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques: Produced

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: The output of the digital FA-I mechanoreceptor (yellow color) implemented on the ZedBoard for (A) spiking and (B) bursting responses. Signals are physically produced and observed on the oscilloscope. The FA-I mechanoreceptor responds with bursting / spiking patterns during stimulus onset and offset (blue color). The volt division for the output (input) channel was set on 500 mV (2V).

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques: Produced

Journal: Frontiers in Neuroscience

Article Title: A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor

doi: 10.3389/fnins.2018.00322

Figure Lengend Snippet: The response of the Merkel spiking model. In each part, the first panel (green) shows the response of the differential Equations (1) and (2) solved by Runge–Kutta method, RK4, the second panel (pink) is the response of the discrete Equations (7) and (8), the third panel (red) illustrates the VIVADO simulation of the digital circuit and the last panel is the response of the digital mechanoreceptor (blue color) executed on the ZedBoard. The last panel also displays the input (yellow color) which its amplitude is for (A) 2.4, (B) 2.6, (C) 2.8, (D) 3 mA. The Time division was set on 25 ms.

Article Snippet: First, in order to achieve an efficient real-time hardware implementation in FPGA, the nonlinear differential equations of the mechanoreceptor spiking model are simulated in MATLAB.

Techniques: