notebooks/03-neo.ipynb

@@ -72,9 +72,9 @@
    },
    "source": [
     "### Neuronal data sources\n",
-    "<img src=\"../images/R2G_arrays.jpg\" width=\"600\"/>\n",
+    "<img src=\"../images/R2G_arrays_L.png\" width=\"700\"/>\n",
     "\n",
-    "Data are recorded from a Utah array implanted in motor cortex of a macaque (monkey N, indicated in red) during a delayed reach to grasp task. Black numbers indicate the electrode IDs, gray numbers indicate the connector-aligned IDs."
+    "Data are recorded from a Utah array implanted in motor cortex of a macaque (monkey L, indicated in yellow) during a delayed reach to grasp task. Black numbers indicate the electrode IDs, gray numbers indicate the connector-aligned IDs."
    ]
   },
   {
@@ -175,8 +175,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "i140703-001.nix  l101210-001.ns2  l101210-001_small_cut_60.0s.nix\r\n",
-      "l101210-001.nev  l101210-001.ns5  LICENSE.txt\r\n"
+      "l101210-001_small_cut_60.0s.nix  LICENSE.txt\r\n"
      ]
     }
    ],
@@ -1075,7 +1074,7 @@
     }
    },
    "source": [
-    "This summary already tells us that we only need to take care of a single segment with one event, one analogsignal and multiple spiketrain objects. The 96 continuously sampled channels are sampled a 'low' sampling rate of 1kHz and contain neural data, so data comparable to local-field potential measurements."
+    "This summary already tells us that we only need to take care of a single segment with three event objects, two analogsignals and multiple spiketrain objects. The 96 continuously sampled channels of the second analogsignal are sampled a 'low' sampling rate of 1kHz and contain neural data, so data comparable to local-field potential measurements."
    ]
   },
   {
@@ -1145,8 +1144,8 @@
    "source": [
     "We see that both, spiketrains as well as channels are annotated with a 'connector_aligned_id', indicating the spatial source of the signal. In addition the coordinates in x and y direction are provided in physical units for each channel and spiketrain. Spiketrains also carry information about 'noise', 'mua' or 'sua' assignment, indicating that the spikes were spikesorted and assigned to one of the three unit categories:\n",
     "- *noise*: non-neural threshold crossing events)\n",
-    "- *mua*: multi-unit-activity - neural threshold crossing events that can not be uniquely assigned to a virtual neuron unit\n",
-    "- *sua*: single-unit-activity - neural threshold crossing events that are assigned to a single virtual neuron unit"
+    "- *mua*: multi-unit-activity - neural threshold crossing events not uniquely assigned to a putative neuron\n",
+    "- *sua*: single-unit-activity - neural threshold crossing events assigned to a single virtual neuron"
    ]
   },
   {
@@ -1840,8 +1839,7 @@
    },
    "outputs": [],
    "source": [
-    "from neo.utils import add_epoch\n",
-    "import quantities as pq"
+    "from neo.utils import add_epoch"
    ]
   },
   {
@@ -1859,7 +1857,7 @@
    },
    "outputs": [],
    "source": [
-    "pre = -10 * pq.ms\n",
+    "pre = -1 * pq.ms\n",
     "post = 15 * pq.ms\n",
     "epoch = add_epoch(\n",
     "    segment,\n",
@@ -1900,7 +1898,7 @@
      "output_type": "stream",
      "text": [
       "Number of epochs: 12\n",
-      "Durations of epochs: [0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025] s\n"
+      "Durations of epochs: [0.016 0.016 0.016 0.016 0.016 0.016 0.016 0.016 0.016 0.016 0.016 0.016] s\n"
      ]
     }
    ],
@@ -2016,7 +2014,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "In the new trial TS is happening at [array(0.00503333) * s, array(0.00493333) * s, array(0.00496667) * s, array(0.005) * s, array(0.01) * s, array(0.00516667) * s, array(0.00496667) * s, array(0.005) * s, array(0.005) * s, array(0.01) * s, array(0.00276667) * s, array(0.00503333) * s]\n"
+      "In the new trial TS is happening at [array(0.001) * s, array(0.001) * s, array(0.001) * s, array(0.001) * s, array(0.001) * s, array(0.001) * s, array(0.001) * s, array(0.001) * s, array(0.001) * s, array(0.001) * s, array(0.001) * s, array(0.001) * s]\n"
      ]
     }
    ],
@@ -2269,16 +2267,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[0.83324227 0.98745161]\n",
-      " [0.23357032 0.59198443]\n",
-      " [0.2467916  0.4852882 ]\n",
-      " [0.71098425 0.85767944]\n",
-      " [0.92749443 0.79997768]\n",
-      " [0.04551666 0.4452905 ]\n",
-      " [0.3194701  0.12393494]\n",
-      " [0.475328   0.087597  ]\n",
-      " [0.94843813 0.75744565]\n",
-      " [0.38120879 0.12582775]] uV\n"
+      "[[0.40313379 0.15227273]\n",
+      " [0.11129528 0.85556261]\n",
+      " [0.69925964 0.15817844]\n",
+      " [0.38584076 0.76434646]\n",
+      " [0.7407746  0.31910149]\n",
+      " [0.48267875 0.09031804]\n",
+      " [0.06789955 0.23879141]\n",
+      " [0.24871353 0.58749449]\n",
+      " [0.15783328 0.0821931 ]\n",
+      " [0.17821349 0.73940646]] uV\n"
      ]
     }
    ],
@@ -2333,16 +2331,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[8.33242266e-07 9.87451609e-07]\n",
-      " [2.33570324e-07 5.91984428e-07]\n",
-      " [2.46791599e-07 4.85288197e-07]\n",
-      " [7.10984247e-07 8.57679440e-07]\n",
-      " [9.27494430e-07 7.99977682e-07]\n",
-      " [4.55166622e-08 4.45290502e-07]\n",
-      " [3.19470101e-07 1.23934940e-07]\n",
-      " [4.75327996e-07 8.75969987e-08]\n",
-      " [9.48438135e-07 7.57445652e-07]\n",
-      " [3.81208791e-07 1.25827752e-07]] V\n"
+      "[[4.03133793e-07 1.52272729e-07]\n",
+      " [1.11295280e-07 8.55562607e-07]\n",
+      " [6.99259635e-07 1.58178437e-07]\n",
+      " [3.85840755e-07 7.64346458e-07]\n",
+      " [7.40774605e-07 3.19101494e-07]\n",
+      " [4.82678750e-07 9.03180435e-08]\n",
+      " [6.78995472e-08 2.38791408e-07]\n",
+      " [2.48713525e-07 5.87494489e-07]\n",
+      " [1.57833277e-07 8.21931030e-08]\n",
+      " [1.78213488e-07 7.39406463e-07]] V\n"
      ]
     }
    ],
@@ -2423,16 +2421,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[0.83324227 0.98745161]\n",
-      " [0.23357032 0.59198443]\n",
-      " [0.2467916  0.4852882 ]\n",
-      " [0.71098425 0.85767944]\n",
-      " [0.92749443 0.79997768]\n",
-      " [0.04551666 0.4452905 ]\n",
-      " [0.3194701  0.12393494]\n",
-      " [0.475328   0.087597  ]\n",
-      " [0.94843813 0.75744565]\n",
-      " [0.38120879 0.12582775]]\n"
+      "[[0.40313379 0.15227273]\n",
+      " [0.11129528 0.85556261]\n",
+      " [0.69925964 0.15817844]\n",
+      " [0.38584076 0.76434646]\n",
+      " [0.7407746  0.31910149]\n",
+      " [0.48267875 0.09031804]\n",
+      " [0.06789955 0.23879141]\n",
+      " [0.24871353 0.58749449]\n",
+      " [0.15783328 0.0821931 ]\n",
+      " [0.17821349 0.73940646]]\n"
      ]
     }
    ],