NetPyNe

27 flashcards · Biology · by lakesare

1. What does createSimulateAnalyze() do? from netpyne import sim sim.createSimulateAnalyze(netParams = HHTut.netParams, simConfig = HHTut.simConfig)

   creates and simulates the network, and save and plot data. It requires the following two arguments:netParams - an object of class NetParams to store network parameters (e.g. cell properties, populations, connectivity)simConfig - an object of class SimConfig to store simulation options (e.g. duration, dt, recording and plotting options, etc.)

2. In createSimulateAnalyze(), what do: netParams, and simConfig accept? from netpyne import sim sim.createSimulateAnalyze(netParams = ?, simConfig = ?)

   netParams - stores network params (cell properties, connections between cells) simConfig - simulation configuration (duration, plotting options) It requires the following two arguments:netParams - an object of class NetParams to store network parameters (e.g. cell properties, populations, connectivity)simConfig - an object of class SimConfig to store simulation options (e.g. duration, dt, recording and plotting options, etc.)

3. Name any 3 dictionaries in the netParams argument. sim.createSimulateAnalyze(netParams = ?, simConfig = ?)

   cellParams - cell types and their associated parameters (e.g. cell geometry) popParams - populations in the network and their parameters synMechParams - synaptic mechanisms and their parameters connParams - network connectivity rules and their associated parameters. subConnParams - network subcellular connectivity rules and their associated parameters. stimSourceParams - stimulation sources parameters. stimTargetParams - mapping between stimulation sources and target cells. rxdParams - reaction…

4. How to add artificial stimulation?

   Use netParams.stimSourceParams['bkg'] = {'type': 'NetStim', 'rate': 10, 'noise': 0.5}

5. What's a pickle in python?

   It's a package for turning Python objects into 101010 files. "Pickling" is the process whereby a Python object hierarchy is converted into a byte stream, and "unpickling" is the inverse operation, whereby a byte stream (from a binary file or bytes-like object) is converted back into an object hierarchy.

6. What neuron model may you want to use to gain speed?

   Izhikevich cell model.

7. What can be here netParams.cellParams['___________']?

   Our custom name for the cells: I (for inhibitory) E (for excitatory) PYR (for pyramidal)

8. What do stimSourceParams VS stimTargetParams do?

   stimSourceParams - stimulation sources stimTargetParams - mapping of sources to cells

9. Name 2 types of the stimulation sources. netParams: { stimSourceParams: { 'Input_1': { 'type': ____________ } } }

   IClamp - current clamp VClamp - voltage clamp AlphaSynapse NetStim We added four typical NEURON sources of stimulation, each of a different type: IClamp, VClamp, AlphaSynapse, NetStim.

10. What's yNorm?

    yNorm & YNormRange are about how deep in the cortex the cell is.

11. Who's this?

    John Hopfield, creator of Hopfield networks (a form of recurrent artificial neural network).

12. What one function can we use instead of all these?

    sim.createSimulateAnalyze(netParams=..., simConfig=...)

13. What's a Hebbian learning?

    When two joined cells fire simultaneously, the connection between them strengthens.

14. Name 2 approaches to hyperparameter optimization in machine learning. In machine learning, hyperparameter optimization or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm.

    Grid search The traditional way of performing hyperparameter optimization has been grid search, or a parameter sweep, which is simply an exhaustive searching through a manually specified subset of the hyperparameter space of a learning algorithm.Random search Random Search replaces the exhaustive enumeration of all combinations by selecting them randomly. Bayesian optimization Gradient-based optimization Evolutionary optimization Population-based

15. Name 1 use of batch simulations in NetPyNe.

    For hyperparameter optimization. # fill in with parameters to explore and range of values (key has to coincide with a variable in simConfig) params['synMechTau2'] = [3.0, 5.0, 7.0] params['connWeight'] = [0.005, 0.01, 0.15] By batch simulations we mean modifying some parameter values within a given range and automatically running simulations for all combinations of these parameter values (also known as grid parameter search).

16. What's OpenMPI? The Open MPI Project is an open source Message Passing Interface.

    It's a program that helps us run NetPyNe in parallel on multiple cores.

17. What does LFP stand for?

    Local Field Potential The soma voltage, LFP time-resolved signal and the 3D locations of the electrodes are plotted.

18. Name 2 neuron models.

    Integrate-and-Fire model A neuron is represented by its membrane voltage V which evolves in time during stimulation with an input current I(t) accordingOne of the earliest models of a neuron is the perfect integrate-and-fire model (also called non-leaky integrate-and-fire), first investigated in 1907 by Louis Lapicque.Hodgkin–Huxley model It consists of a set of nonlinear differential equations describing the behaviour of ion channels that permeate the cell membrane of the squid giant axon.Hodg…

19. [NetPyNe] What is this?

    It's a population of 40 cells. Each cell has a soma, and a long dendrite.

20. How can you access the Neuron object from NetPyNE?

    Use .hObj

21. Is it possible to have different cell types in the same population?

    Not in GUI, but yes programmatically.

22. .py VS .hoc files?

    .hoc is older format for NEURON, we should use Python now. HOC is an older interpreter language for neuron before we could use python, so now you shouldn't use hoc for anything.

23. What does INT stand for?

    Interneuron.

24. What is 'VSoma'?

    It's an arbitrary name of the trace. Each entry in recordTraces is also a dictionary, whose key is the name of the trace (an arbitrary string you may choose) and whose value is a dictionary with the specifications of the desired trace.

25. What would this record? simConfig.recordTraces['dend_Na'] = { "sec": "dend", "loc": 1.0, "var": "nai" }

    It records the sodium concentration at the distal end of the 'dend' section.

26. [NetPyNE] Where can we find info about the cellModel 'IntFire2'?

    In Neuron docs: These cells are implemented as .mod files, and these .mod files are a part of Neuron. Other cellModels:

27. Histogram VS bar charts?

    Histogram - continuous data subdivided into ranges. Histogram is subdivided into bins, where the bins represent ranges of data.Bar chart - is a plot of categories. Some authors recommend that bar charts have gaps between the rectangles to clarify the distinction.