diff --git a/sinabs/layers/lif.py b/sinabs/layers/lif.py
index 711d5c6f..3275e6e4 100644
--- a/sinabs/layers/lif.py
+++ b/sinabs/layers/lif.py
@@ -93,18 +93,22 @@ def __init__(
                 if tau_syn is not None
                 else None
             )
-        self.spike_threshold = (
-            torch.tensor(spike_threshold)
-            if type(spike_threshold) == float
-            else spike_threshold
-        )
         self.spike_fn = spike_fn
         self.reset_fn = reset_fn
         self.surrogate_grad_fn = surrogate_grad_fn
-        self.min_v_mem = min_v_mem
         self.train_alphas = train_alphas
         self.norm_input = norm_input
         self.record_states = record_states
+        self.min_v_mem = (
+            nn.Parameter(torch.as_tensor(min_v_mem), requires_grad=False)
+            if min_v_mem
+            else None
+        )
+        self.spike_threshold = (
+            nn.Parameter(torch.as_tensor(spike_threshold), requires_grad=False)
+            if spike_threshold
+            else None
+        )
         if shape:
             self.init_state_with_shape(shape)
 
diff --git a/tests/test_iaf.py b/tests/test_iaf.py
index eb1cf9b1..f27af198 100644
--- a/tests/test_iaf.py
+++ b/tests/test_iaf.py
@@ -10,9 +10,11 @@
 def test_iaf_basic():
     batch_size, time_steps = 10, 100
     input_current = torch.rand(batch_size, time_steps, 2, 7, 7)
-    layer = IAF()
+    layer = IAF(min_v_mem=-2.0)
     spike_output = layer(input_current)
 
+    assert "min_v_mem" in layer.state_dict().keys()
+    assert "spike_threshold" in layer.state_dict().keys()
     assert layer.does_spike
     assert input_current.shape == spike_output.shape
     assert torch.isnan(spike_output).sum() == 0
diff --git a/tests/test_lif.py b/tests/test_lif.py
index 15c6a6bb..74c23003 100644
--- a/tests/test_lif.py
+++ b/tests/test_lif.py
@@ -15,7 +15,7 @@ def test_lif_basic():
     tau_mem = torch.tensor(20.0)
     alpha = torch.exp(-1 / tau_mem)
     input_current = torch.rand(batch_size, time_steps, 2, 7, 7) / (1 - alpha)
-    layer = LIF(tau_mem=tau_mem)
+    layer = LIF(tau_mem=tau_mem, min_v_mem=-2.0)
     spike_output = layer(input_current)
 
     # Make sure __repr__ works
@@ -24,6 +24,8 @@ def test_lif_basic():
     # Make sure arg_dict works
     layer.arg_dict
 
+    assert "min_v_mem" in layer.state_dict().keys()
+    assert "spike_threshold" in layer.state_dict().keys()
     assert layer.does_spike
     assert input_current.shape == spike_output.shape
     assert torch.isnan(spike_output).sum() == 0