diff --git a/CHANGELOG.md b/CHANGELOG.md
index 880ab649..3cd37b6f 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -2,6 +2,8 @@
 
 ### New Checks
 * Added `check_file_extension` for NWB file extension best practice recommendations (`.nwb`, `.nwb.h5`, or `.nwb.zarr`) [#625](https://github.com/NeurodataWithoutBorders/nwbinspector/pull/625)
+* Added `check_time_series_duration` to detect unusually long TimeSeries durations (default threshold: 1 year). [#627](https://github.com/NeurodataWithoutBorders/nwbinspector/pull/627)
+* Added `check_rate_not_below_threshold` to detect suspiciously low sampling rates that may indicate period was used instead of rate. [#627](https://github.com/NeurodataWithoutBorders/nwbinspector/pull/627)
 
 ### Improvements
 * Added documentation to API and CLI docs on how to use the dandi config option. [#624](https://github.com/NeurodataWithoutBorders/nwbinspector/pull/624)
diff --git a/src/nwbinspector/checks/__init__.py b/src/nwbinspector/checks/__init__.py
index 3011d187..63b5cae7 100644
--- a/src/nwbinspector/checks/__init__.py
+++ b/src/nwbinspector/checks/__init__.py
@@ -82,8 +82,10 @@
     check_missing_unit,
     check_rate_is_not_zero,
     check_rate_is_positive,
+    check_rate_not_below_threshold,
     check_regular_timestamps,
     check_resolution,
+    check_time_series_duration,
     check_timestamp_of_the_first_sample_is_not_negative,
     check_timestamps_ascending,
     check_timestamps_match_first_dimension,
@@ -151,6 +153,8 @@
     "check_timestamps_match_first_dimension",
     "check_timestamp_of_the_first_sample_is_not_negative",
     "check_rate_is_not_zero",
+    "check_rate_not_below_threshold",
+    "check_time_series_duration",
     "check_intracellular_electrode_cell_id_exists",
     "check_compass_direction_unit",
     "check_spatial_series_radians_magnitude",
diff --git a/src/nwbinspector/checks/_time_series.py b/src/nwbinspector/checks/_time_series.py
index dc3ea083..ac6de544 100644
--- a/src/nwbinspector/checks/_time_series.py
+++ b/src/nwbinspector/checks/_time_series.py
@@ -202,3 +202,76 @@ def check_rate_is_positive(time_series: TimeSeries) -> Optional[InspectorMessage
         )
 
     return None
+
+
+@register_check(importance=Importance.BEST_PRACTICE_SUGGESTION, neurodata_type=TimeSeries)
+def check_time_series_duration(
+    time_series: TimeSeries, duration_threshold: float = 31557600.0
+) -> Optional[InspectorMessage]:
+    """
+    Check if the TimeSeries duration is longer than the specified threshold.
+
+    The default threshold is 1 year (31,557,600 seconds = 365.25 days).
+    Duration is calculated from either timestamps or starting_time + rate + data length.
+    """
+    if time_series.data is None:
+        return None
+
+    data_shape = get_data_shape(time_series.data)
+    if data_shape is None or data_shape[0] <= 1:
+        return None
+
+    duration = None
+
+    # Calculate duration from timestamps if available
+    if time_series.timestamps is not None:
+        timestamps_shape = get_data_shape(time_series.timestamps)
+        if timestamps_shape is not None and timestamps_shape[0] > 1:
+            first_timestamp = time_series.timestamps[0]
+            last_timestamp = time_series.timestamps[-1]
+            duration = float(last_timestamp - first_timestamp)
+
+    # Calculate duration from starting_time and rate if timestamps not available
+    elif time_series.rate is not None and time_series.rate > 0:
+        num_samples = data_shape[0]
+        duration = (num_samples - 1) / time_series.rate
+
+    # If we have a duration, check if it exceeds the threshold
+    if duration is not None and duration > duration_threshold:
+        # Convert duration to years for the message
+        duration_years = duration / 31557600.0
+        return InspectorMessage(
+            message=(
+                f"TimeSeries '{time_series.name}' has an unusually long duration of {duration:.2f} seconds ({duration_years:.2f} years), "
+                f"which may indicate an error in the timestamps or rate data. "
+                "Please verify that this is correct."
+            )
+        )
+
+    return None
+
+
+@register_check(importance=Importance.BEST_PRACTICE_VIOLATION, neurodata_type=TimeSeries)
+def check_rate_not_below_threshold(
+    time_series: TimeSeries, low_rate_threshold: float = 0.01
+) -> Optional[InspectorMessage]:
+    """
+    Check if the sampling rate is suspiciously low (below threshold, default 0.01 Hz).
+
+    A very low rate likely indicates the period (time between samples) was provided instead of the frequency.
+    The default threshold of 0.01 Hz corresponds to a period of 100 seconds.
+    """
+    if not hasattr(time_series, "rate"):
+        return None
+
+    if time_series.rate is not None and 0 < time_series.rate < low_rate_threshold:
+        period = 1.0 / time_series.rate
+        return InspectorMessage(
+            message=(
+                f"TimeSeries '{time_series.name}' has a sampling rate of {time_series.rate}Hz (period of {period:.2f} seconds). "
+                "This low sampling rate may indicate that the period was specified instead of the rate. "
+                f"If the intended period is {time_series.rate} seconds, the rate should be {1.0 / time_series.rate}Hz."
+            )
+        )
+
+    return None
diff --git a/tests/unit_tests/test_time_series.py b/tests/unit_tests/test_time_series.py
index ef96e312..7787b22f 100644
--- a/tests/unit_tests/test_time_series.py
+++ b/tests/unit_tests/test_time_series.py
@@ -8,8 +8,10 @@
     check_missing_unit,
     check_rate_is_not_zero,
     check_rate_is_positive,
+    check_rate_not_below_threshold,
     check_regular_timestamps,
     check_resolution,
+    check_time_series_duration,
     check_timestamp_of_the_first_sample_is_not_negative,
     check_timestamps_ascending,
     check_timestamps_match_first_dimension,
@@ -413,3 +415,193 @@ def test_check_rate_is_positive_fail():
         object_name="TimeSeriesTest",
         location="/",
     )
+
+
+def test_check_time_series_duration_pass_short_duration_with_timestamps():
+    """Test that a short duration TimeSeries with timestamps passes."""
+    time_series = pynwb.TimeSeries(
+        name="test_time_series",
+        unit="test_units",
+        data=np.zeros(shape=100),
+        timestamps=np.linspace(0, 100, 100),  # 100 seconds, much less than 1 year
+    )
+    assert check_time_series_duration(time_series) is None
+
+
+def test_check_time_series_duration_pass_short_duration_with_rate():
+    """Test that a short duration TimeSeries with rate passes."""
+    time_series = pynwb.TimeSeries(
+        name="test_time_series",
+        unit="test_units",
+        data=np.zeros(shape=1000),
+        starting_time=0.0,
+        rate=10.0,  # 1000 samples at 10Hz = 100 seconds
+    )
+    assert check_time_series_duration(time_series) is None
+
+
+def test_check_time_series_duration_fail_with_timestamps():
+    """Test that a TimeSeries exceeding 1 year duration with timestamps fails."""
+    # Create timestamps spanning more than 1 year (31557600 seconds)
+    one_year = 31557600.0
+    time_series = pynwb.TimeSeries(
+        name="long_time_series",
+        unit="test_units",
+        data=np.zeros(shape=100),
+        timestamps=np.linspace(0, one_year + 1000, 100),  # Exceeds 1 year
+    )
+    duration = one_year + 1000
+    duration_years = duration / 31557600.0
+    expected_message = (
+        f"TimeSeries 'long_time_series' has an unusually long duration of {duration:.2f} seconds ({duration_years:.2f} years), "
+        f"which may indicate an error in the timestamps or rate data. "
+        "Please verify that this is correct."
+    )
+    assert check_time_series_duration(time_series) == InspectorMessage(
+        message=expected_message,
+        importance=Importance.BEST_PRACTICE_SUGGESTION,
+        check_function_name="check_time_series_duration",
+        object_type="TimeSeries",
+        object_name="long_time_series",
+        location="/",
+    )
+
+
+def test_check_time_series_duration_fail_with_rate():
+    """Test that a TimeSeries exceeding 1 year duration with rate fails."""
+    # Create a time series with more than 1 year of data
+    # Use a lower rate to avoid creating a large array
+    one_year = 31557600.0
+    rate = 0.01  # 0.01 Hz = one sample every 100 seconds
+    num_samples = int((one_year + 1000) * rate) + 1  # Minimal samples needed
+    time_series = pynwb.TimeSeries(
+        name="long_time_series",
+        unit="test_units",
+        data=np.zeros(shape=num_samples),
+        starting_time=0.0,
+        rate=rate,
+    )
+    duration = (num_samples - 1) / rate
+    duration_years = duration / 31557600.0
+    expected_message = (
+        f"TimeSeries 'long_time_series' has an unusually long duration of {duration:.2f} seconds ({duration_years:.2f} years), "
+        f"which may indicate an error in the timestamps or rate data. "
+        "Please verify that this is correct."
+    )
+    assert check_time_series_duration(time_series) == InspectorMessage(
+        message=expected_message,
+        importance=Importance.BEST_PRACTICE_SUGGESTION,
+        check_function_name="check_time_series_duration",
+        object_type="TimeSeries",
+        object_name="long_time_series",
+        location="/",
+    )
+
+
+def test_check_time_series_duration_pass_custom_threshold():
+    """Test that the custom duration threshold works correctly."""
+    # Create a TimeSeries with 200 seconds duration
+    time_series = pynwb.TimeSeries(
+        name="test_time_series",
+        unit="test_units",
+        data=np.zeros(shape=100),
+        timestamps=np.linspace(0, 200, 100),
+    )
+    # Should fail with a threshold of 100 seconds
+    result = check_time_series_duration(time_series, duration_threshold=100.0)
+    assert result is not None
+
+    # Should pass with a threshold of 300 seconds
+    result = check_time_series_duration(time_series, duration_threshold=300.0)
+    assert result is None
+
+
+def test_check_time_series_duration_pass_single_sample():
+    """Test that TimeSeries with a single sample passes."""
+    time_series = pynwb.TimeSeries(
+        name="test_time_series",
+        unit="test_units",
+        data=np.zeros(shape=1),
+        timestamps=[0],
+    )
+    assert check_time_series_duration(time_series) is None
+
+
+def test_check_rate_not_below_threshold_pass_normal_rate():
+    """Test that a normal sampling rate passes."""
+    time_series = pynwb.TimeSeries(
+        name="test_time_series",
+        unit="test_units",
+        data=np.zeros(shape=100),
+        starting_time=0.0,
+        rate=30.0,  # 30 Hz is a normal rate
+    )
+    assert check_rate_not_below_threshold(time_series) is None
+
+
+def test_check_rate_not_below_threshold_fail_very_low_rate():
+    """Test that a very low sampling rate fails."""
+    low_rate = 0.001  # 0.001 Hz = period of 1000 seconds
+    time_series = pynwb.TimeSeries(
+        name="test_time_series",
+        unit="test_units",
+        data=np.zeros(shape=100),
+        starting_time=0.0,
+        rate=low_rate,
+    )
+    period = 1.0 / low_rate
+    expected_message = (
+        f"TimeSeries 'test_time_series' has a sampling rate of {low_rate}Hz (period of {period:.2f} seconds). "
+        "This low sampling rate may indicate that the period was specified instead of the rate. "
+        f"If the intended period is {low_rate} seconds, the rate should be {1.0 / low_rate}Hz."
+    )
+    assert check_rate_not_below_threshold(time_series) == InspectorMessage(
+        message=expected_message,
+        importance=Importance.BEST_PRACTICE_VIOLATION,
+        check_function_name="check_rate_not_below_threshold",
+        object_type="TimeSeries",
+        object_name="test_time_series",
+        location="/",
+    )
+
+
+def test_check_rate_not_below_threshold_pass_custom_threshold():
+    """Test that custom threshold works correctly."""
+    time_series = pynwb.TimeSeries(
+        name="test_time_series",
+        unit="test_units",
+        data=np.zeros(shape=100),
+        starting_time=0.0,
+        rate=0.005,  # Below default threshold of 0.01
+    )
+    # Should fail with default threshold
+    result = check_rate_not_below_threshold(time_series)
+    assert result is not None
+
+    # Should pass with lower custom threshold
+    result = check_rate_not_below_threshold(time_series, low_rate_threshold=0.001)
+    assert result is None
+
+
+def test_check_rate_not_below_threshold_pass_no_rate():
+    """Test that TimeSeries without rate attribute passes."""
+    time_series = pynwb.TimeSeries(
+        name="test_time_series",
+        unit="test_units",
+        data=np.zeros(shape=100),
+        timestamps=np.linspace(0, 100, 100),
+    )
+    assert check_rate_not_below_threshold(time_series) is None
+
+
+def test_check_rate_not_below_threshold_pass_zero_rate():
+    """Test that zero rate passes (handled by different check)."""
+    time_series = pynwb.TimeSeries(
+        name="test_time_series",
+        unit="test_units",
+        data=np.zeros(shape=1),
+        starting_time=0.0,
+        rate=0.0,
+    )
+    # Zero rate should pass this check (it's handled by check_rate_is_not_zero)
+    assert check_rate_not_below_threshold(time_series) is None