caglorithm

neurolib tutorial

A tutorial for neurolib will be held at the CNS*2022 satellite tutorials.

This tutorial is intended researchers interested in learning how to use neurolib for simulating, exploring, and optimizing neural mass models and whole-brain networks.

Registration

Registration for the satellite tutorials is free, but required. Register here 👈.

caglorithm

import numpy as np

aal2 = {
    1: "Precentral_L",
    2: "Precentral_R",
    3: "Frontal_Sup_2_L",
    4: "Frontal_Sup_2_R",
    5: "Frontal_Mid_2_L",
    6: "Frontal_Mid_2_R",
    7: "Frontal_Inf_Oper_L",

caglorithm

import pandas as pd
import matplotlib.pyplot as plt
import datetime
import matplotlib.dates as mdates

table_urls = ["https://www.wahlrecht.de/umfragen/allensbach.htm",
              "https://www.wahlrecht.de/umfragen/emnid.htm",
              "https://www.wahlrecht.de/umfragen/forsa.htm",
              "https://www.wahlrecht.de/umfragen/politbarometer.htm",
              "https://www.wahlrecht.de/umfragen/gms.htm",

caglorithm

import numpy as np
plt.rcParams['image.cmap'] = 'plasma'
import matplotlib.pyplot as plt
from neurolib.utils.loadData import Dataset
ds = Dataset("hcp")

mat_orig = ds.Cmats[0]

N = mat_orig.shape[0]

caglorithm

from neurolib.models.aln import ALNModel
from neurolib.utils.loadData import Dataset
from neurolib.optimize.exploration import BoxSearch
from neurolib.utils.parameterSpace import ParameterSpace

# load brain scan dataset
ds = Dataset("hcp")
# initialize brain network model
model = ALNModel(Cmat = ds.Cmat, Dmat = ds.Dmat)
# 5 minute simulation