diff --git a/CI/unit_tests/recorders/test_base_recorder.py b/CI/unit_tests/recorders/test_base_recorder.py
index eff66ad..4708859 100644
--- a/CI/unit_tests/recorders/test_base_recorder.py
+++ b/CI/unit_tests/recorders/test_base_recorder.py
@@ -109,6 +109,7 @@ def test_init(self):
         assert recorder.storage_path == storage_path
         assert recorder.measurements == [self.measurement_1, self.measurement_2]
         assert recorder.chunk_size == 10
+        assert recorder.overwrite is False
 
     def test_neural_state_keys(self):
         """
@@ -181,7 +182,10 @@ def test_store(self):
         name = "test"
         storage_path = "temp/"
         recorder = BaseRecorder(
-            name, storage_path, [self.measurement_1, self.measurement_2], 10
+            name,
+            storage_path,
+            [self.measurement_1, self.measurement_2],
+            10,
         )
 
         # Test storing
@@ -202,6 +206,18 @@ def test_store(self):
         print(data["dummy_1"].shape)
         assert_array_equal(data["dummy_1"], np.ones(shape=(2, 3, 10, 5)))
         assert_array_equal(data["dummy_2"], 10 * np.ones(shape=(2, 3, 10)))
+        # _results should be empty after storing
+        assert recorder._results == {"dummy_1": [], "dummy_2": []}
+
+        # test overwriting
+        recorder.overwrite = True
+        recorder._measure(**self.neural_state)
+        recorder._store(20)
+        data = recorder.load()
+
+        assert set(data.keys()) == {"dummy_1", "dummy_2"}
+        assert_array_equal(data["dummy_1"], np.ones(shape=(1, 3, 10, 5)))
+        assert_array_equal(data["dummy_2"], 10 * np.ones(shape=(1, 3, 10)))
 
         # Delete temporary directory
         os.system("rm -r temp/")
diff --git a/papyrus/recorders/base_recorder.py b/papyrus/recorders/base_recorder.py
index 2d93e98..7712974 100644
--- a/papyrus/recorders/base_recorder.py
+++ b/papyrus/recorders/base_recorder.py
@@ -63,6 +63,7 @@ def __init__(
         storage_path: str,
         measurements: List[BaseMeasurement],
         chunk_size: int,
+        overwrite: bool = False,
     ):
         """
         Constructor method of the BaseRecorder class.
@@ -78,21 +79,33 @@ def __init__(
                 The measurements that the recorder will apply.
         chunk_size : int
                 The size of the chunks in which the data will be stored.
+        overwrite : bool (default=False)
+                Whether to overwrite the existing data in the database.
         """
         self.name = name
         self.storage_path = storage_path
         self.measurements = measurements
         self.chunk_size = chunk_size
+        self.overwrite = overwrite
 
         # Read in neural state keys from measurements
-        self.neural_state_keys = []
-        for measurement in measurements:
-            self.neural_state_keys.extend(measurement.neural_state_keys)
-        self.neural_state_keys = list(set(self.neural_state_keys))
+        self._read_neural_state_keys()
 
         # Temporary storage for results
         self._init_results()
 
+    def _read_neural_state_keys(self):
+        """
+        Read the neural state keys from the measurements.
+
+        Updates the neural_state_keys attribute of the recorder with the keys of the
+        neural state that the measurements take as input.
+        """
+        self.neural_state_keys = []
+        for measurement in self.measurements:
+            self.neural_state_keys.extend(measurement.neural_state_keys)
+        self.neural_state_keys = list(set(self.neural_state_keys))
+
     def _init_results(self):
         """
         Initialize the temporary storage for the results.
@@ -169,8 +182,11 @@ def _store(self, epoch: int):
             try:
                 data = self.load()
                 # Append the new data
-                for key in self._results.keys():
-                    data[key] = np.append(data[key], self._results[key], axis=0)
+                if self.overwrite:
+                    data = self._results
+                else:
+                    for key in self._results.keys():
+                        data[key] = np.append(data[key], self._results[key], axis=0)
             # If the file does not exist, create a new one
             except FileNotFoundError:
                 data = self._results