diff --git a/neo/rawio/intanrawio.py b/neo/rawio/intanrawio.py
index e7d668f14..5f2fef7a5 100644
--- a/neo/rawio/intanrawio.py
+++ b/neo/rawio/intanrawio.py
@@ -530,6 +530,57 @@ def _demultiplex_digital_data(self, raw_digital_data, channel_ids, i_start, i_st
             output[:, channel_index] = demultiplex_data[i_start:i_stop].flatten()
 
         return output
+    
+    def get_intan_timestamps(self, i_start=None, i_stop=None):
+        """
+        Retrieves the sample indices from the Intan raw data within a specified range.
+        
+        Note that sample indices are called timestamps in the Intan format but they are 
+        in fact just sample indices. This function extracts the sample index timestamps 
+        from Intan files, which represent  relative time points in sample units (not absolute time).
+        These indices can be  particularly useful when working with recordings that have discontinuities.
+        
+        Parameters
+        ----------
+        i_start : int, optional
+            The starting index from which to retrieve sample indices. If None, starts from 0.
+        i_stop : int, optional
+            The stopping index up to which to retrieve sample indices (exclusive). 
+            If None, retrieves all available indices from i_start onward.
+        
+        Returns
+        -------
+        timestamps : ndarray
+            The flattened array of sample indices within the specified range.
+            
+        Notes
+        -----
+        - Sample indices can be converted to seconds by dividing by the sampling rate of the amplifier stream.
+        - The function automatically handles different file formats:
+        * header-attached: Timestamps are extracted directly from the timestamp field
+        * one-file-per-signal: Timestamps are read from the timestamp stream
+        * one-file-per-channel: Timestamps are read from the first channel in the timestamp stream
+        - When recordings have discontinuities (indicated by the `discontinuous_timestamps` 
+        attribute being True), these indices allow for proper temporal alignment of the data.
+        """
+        if i_start is None:
+            i_start = 0
+        
+        # Get the timestamps based on file format
+        if self.file_format == "header-attached":
+            timestamps = self._raw_data["timestamp"]
+        elif self.file_format == "one-file-per-signal":
+            timestamps = self._raw_data["timestamp"]
+        elif self.file_format == "one-file-per-channel":
+            timestamps = self._raw_data["timestamp"][0]
+
+        # TODO if possible ensure that timestamps memmaps are always of correct shape to avoid memory copy here.
+        timestamps = timestamps.flatten() if timestamps.ndim > 1 else timestamps
+        
+        if i_stop is None:
+            return timestamps[i_start:]
+        else:
+            return timestamps[i_start:i_stop]
 
     def _assert_timestamp_continuity(self):
         """
@@ -545,26 +596,11 @@ def _assert_timestamp_continuity(self):
         NeoReadWriteError
             If timestamps are not continuous and `ignore_integrity_checks` is False.
             The error message includes a table detailing the discontinuities found.
-
-        Notes
-        -----
-        The method extracts timestamps from the raw data based on the file format:
-
-        * **header-attached:** Timestamps are extracted from a 'timestamp' field in the raw data.
-        * **one-file-per-signal:** Timestamps are taken from the last stream.
-        * **one-file-per-channel:** Timestamps are retrieved from the first channel of the last stream.
         """
         # check timestamp continuity
-        if self.file_format == "header-attached":
-            timestamp = self._raw_data["timestamp"].flatten()
-
-        # timestamps are always last stream for headerless binary files
-        elif self.file_format == "one-file-per-signal":
-            timestamp = self._raw_data["timestamp"]
-        elif self.file_format == "one-file-per-channel":
-            timestamp = self._raw_data["timestamp"][0]
+        timestamps = self.get_intan_timestamps()
 
-        discontinuous_timestamps = np.diff(timestamp) != 1
+        discontinuous_timestamps = np.diff(timestamps) != 1
         timestamps_are_not_contiguous = np.any(discontinuous_timestamps)
         if timestamps_are_not_contiguous:
             # Mark a flag that can be checked after parsing the header to see if the timestamps are continuous or not
@@ -582,8 +618,8 @@ def _assert_timestamp_continuity(self):
 
                 amplifier_sampling_rate = self._global_info["sampling_rate"]
                 for discontinuity_index in np.where(discontinuous_timestamps)[0]:
-                    prev_ts = timestamp[discontinuity_index]
-                    next_ts = timestamp[discontinuity_index + 1]
+                    prev_ts = timestamps[discontinuity_index]
+                    next_ts = timestamps[discontinuity_index + 1]
                     time_diff = (next_ts - prev_ts) / amplifier_sampling_rate
 
                     error_msg += (