diff --git a/src/nwb2bids/bids_models/_channels.py b/src/nwb2bids/bids_models/_channels.py
index 433d9faa..20321c81 100644
--- a/src/nwb2bids/bids_models/_channels.py
+++ b/src/nwb2bids/bids_models/_channels.py
@@ -9,6 +9,7 @@
 import pynwb
 import typing_extensions
 
+from ._model_utils import _build_json_sidecar
 from ..bids_models._base_metadata_model import BaseMetadataContainerModel, BaseMetadataModel
 from ..notifications import Notification
 
@@ -40,26 +41,149 @@ def _infer_scalar_field(
 
 
 class Channel(BaseMetadataModel):
-    name: str
-    electrode_name: str
-    type: str = "n/a"
-    units: str = "V"
-    sampling_frequency: float | None = None
-    low_cutoff: float | None = None
-    high_cutoff: float | None = None
-    reference: str | None = None
-    notch: str | None = None
-    channel_label: str | None = None
-    stream_id: str | None = None
-    description: str | None = None
-    software_filter_types: str | None = None
-    status: typing.Literal["good", "bad"] | None = None
-    status_description: str | None = None
-    gain: float | None = None
-    time_offset: float | None = None
-    time_reference_channel: str | None = None
-    ground: str | None = None
-    recording_mode: str | None = None
+    name: str = pydantic.Field(
+        description="Label of the channel.",
+        title="Channel name",
+    )
+    electrode_name: str = pydantic.Field(
+        description=(
+            "Name of the electrode contact point. The value MUST match a name entry in the corresponding "
+            "*_electrodes.tsv file, linking this channel to its associated electrode contact point. "
+            "For channels not associated with an electrode, use n/a."
+        ),
+        title="Electrode name",
+    )
+    type: str = pydantic.Field(
+        description=(
+            "Type of channel; MUST use the channel types listed below. Note that the type MUST be in upper-case."
+        ),
+        title="Type",
+        default="n/a",
+    )
+    units: str = pydantic.Field(
+        description=(
+            "Physical unit of the value represented in this channel, for example, V for Volt, or fT/cm for femto Tesla "
+            "per centimeter (see Units)."
+        ),
+        title="Units",
+        default="V",
+    )
+    sampling_frequency: float | None = pydantic.Field(
+        description="Sampling rate of the channel in Hz.",
+        title="Sampling frequency",
+        default=None,
+    )
+    low_cutoff: float | None = pydantic.Field(
+        description=(
+            "Frequencies used for the high-pass filter applied to the channel in Hz. If no high-pass "
+            "filter applied, use n/a."
+        ),
+        title="Low cutoff",
+        default=None,
+    )
+    high_cutoff: float | None = pydantic.Field(
+        description=(
+            "Frequencies used for the low-pass filter applied to the channel in Hz. "
+            "If no low-pass filter applied, use n/a. Note that hardware anti-aliasing in A/D conversion of "
+            "all MEG/EEG/EMG electronics applies a low-pass filter; specify its frequency here if applicable."
+        ),
+        title="High cutoff",
+        default=None,
+    )
+    reference: str | None = pydantic.Field(
+        description=(
+            "The reference for the given channel. When the reference is an electrode in *_electrodes.tsv, "
+            'use the name of that electrode. If a corresponding electrode is not applicable, use "n/a".'
+        ),
+        title="Reference",
+        default=None,
+    )
+    notch: str | None = pydantic.Field(
+        description=(
+            "Frequencies used for the notch filter applied to the channel, in Hz. "
+            "If notch filters are applied at multiple frequencies, these frequencies MAY be specified as a list, "
+            "for example, [60, 120, 180]. If no notch filter was applied, use n/a."
+        ),
+        title="Notch",
+        default=None,
+    )
+    channel_label: str | None = pydantic.Field(
+        description=(
+            "Human readable identifier. Use this name to specify the content of signals not generated by electrodes. "
+            "For example, 'DAQ internal synchronization signals', 'behavioral signals', 'behavioral cues'."
+        ),
+        title="Channel label",
+        default=None,
+    )
+    stream_id: str | None = pydantic.Field(
+        description="Data stream of the recording the signal.",
+        title="Stream ID",
+        default=None,
+    )
+    description: str | None = pydantic.Field(
+        description="Brief free-text description of the channel, or other information of interest.",
+        title="Description",
+        default=None,
+    )
+    software_filter_types: str | None = pydantic.Field(
+        description=(
+            "The types of software filters applied to this channel. "
+            "The Levels for this column SHOULD be defined in the accompanying *_channels.json file, "
+            "mapping each filter type key to its description. Use n/a if no software filters were "
+            "applied to this channel."
+        ),
+        title="Software filter types",
+        default=None,
+    )
+    status: typing.Literal["good", "bad", "n/a"] | None = pydantic.Field(
+        description=(
+            "Data quality observed on the channel. "
+            "A channel is considered bad if its data quality is compromised by excessive noise. "
+            "If quality is unknown, then a value of n/a may be used. Description of noise type SHOULD "
+            "be provided in [status_description]."
+        ),
+        title="Status",
+        default=None,
+    )
+    status_description: str | None = pydantic.Field(
+        description=(
+            "Freeform text description of noise or artifact affecting data quality on the channel. "
+            "It is meant to explain why the channel was declared bad in the status column."
+        ),
+        title="Status description",
+        default=None,
+    )
+    gain: float | None = pydantic.Field(
+        description=(
+            "Amplification factor applied from signal detection at the electrode to the signal stored in the data file."
+            " If no gain factor is provided it is assumed to be 1."
+        ),
+        title="Gain",
+        default=None,
+    )
+    time_offset: float | None = pydantic.Field(
+        description="Time shift between signal of this channel to a reference channel in seconds.",
+        title="Time offset",
+        default=None,
+    )
+    time_reference_channel: str | None = pydantic.Field(
+        description="Name of the channel that is used for time alignment of signals.",
+        title="Time reference channel",
+        default=None,
+    )
+    ground: str | None = pydantic.Field(
+        description=(
+            "Information on the ground. For example, 'chamber screw', 'head post', 'ear clip'. "
+            "Only should be used to optionally override the global ground in the _ecephys.json or _icephys.json file."
+        ),
+        title="Ground",
+        default=None,
+    )
+    recording_mode: str | None = pydantic.Field(
+        description="The mode of recording for patch clamp datasets (for example, voltage clamp, current clamp).",
+        title="Recording mode",
+        default=None,
+    )
 
 
 class ChannelTable(BaseMetadataContainerModel):
@@ -246,9 +370,9 @@ def to_json(self, file_path: str | pathlib.Path) -> None:
         file_path : path
             The path to the output JSON file.
         """
+        file_path = pathlib.Path(file_path)
+
+        json_content = _build_json_sidecar(models=self.channels)
+
         with file_path.open(mode="w") as file_stream:
-            json.dump(
-                obj=dict(),  # TODO
-                fp=file_stream,
-                indent=4,
-            )
+            json.dump(obj=json_content, fp=file_stream, indent=4)
diff --git a/src/nwb2bids/bids_models/_electrodes.py b/src/nwb2bids/bids_models/_electrodes.py
index c3ab2448..4729df0d 100644
--- a/src/nwb2bids/bids_models/_electrodes.py
+++ b/src/nwb2bids/bids_models/_electrodes.py
@@ -8,6 +8,7 @@
 import pynwb
 import typing_extensions
 
+from ._model_utils import _build_json_sidecar
 from ..bids_models._base_metadata_model import BaseMetadataContainerModel, BaseMetadataModel
 from ..notifications import Notification
 
@@ -15,21 +16,105 @@
 
 
 class Electrode(BaseMetadataModel):
-    name: str
-    probe_name: str
-    x: float = numpy.nan
-    y: float = numpy.nan
-    z: float = numpy.nan
-    hemisphere: str = "n/a"
-    impedance: float = numpy.nan  # in kOhms
-    shank_id: str = "n/a"
-    size: float | None = None  # in square micrometers
-    electrode_shape: str | None = None
-    material: str | None = None
-    location: str | None = None
-    pipette_solution: str | None = None
-    internal_pipette_diameter: float | None = None  # in micrometers
-    external_pipette_diameter: float | None = None  # in micrometers
+    name: str = pydantic.Field(
+        description="Name of the electrode contact point.",
+        title="Electrode name",
+    )
+    probe_name: str = pydantic.Field(
+        description=(
+            "A unique identifier of the probe, can be identical with the device_serial_number. "
+            "The value MUST match a probe_name entry in the corresponding *_probes.tsv file, linking this electrode "
+            "to its associated probe. For electrodes not associated with a probe, use n/a."
+        ),
+        title="Probe name",
+    )
+    x: float = pydantic.Field(
+        description=(
+            "Recorded position along the x-axis. When no space-<label> entity is used in the filename, "
+            "the position along the local width-axis relative to the probe origin "
+            "(see coordinate_reference_point in *_probes.tsv) in micrometers (um). "
+            "When a space-<label> entity is used in the filename, the position relative to the origin of the "
+            "coordinate system along the first axis. Units are specified by MicroephysCoordinateUnits in the "
+            "corresponding *_coordsystem.json file."
+        ),
+        title="x",
+        default=numpy.nan,
+    )
+    y: float = pydantic.Field(
+        description=(
+            "Recorded position along the y-axis. When no space-<label> entity is used in the filename, "
+            "the position along the local height-axis relative to the probe origin "
+            "(see coordinate_reference_point in *_probes.tsv) in micrometers (um). "
+            "When a space-<label> entity is used in the filename, the position relative to the origin of the "
+            "coordinate system along the second axis. Units are specified by MicroephysCoordinateUnits in the "
+            "corresponding *_coordsystem.json file."
+        ),
+        title="y",
+        default=numpy.nan,
+    )
+    z: float = pydantic.Field(
+        description=(
+            "Recorded position along the z-axis. For 2D electrode localizations, "
+            "this SHOULD be a column of n/a values. "
+            "When no space-<label> entity is used in the filename, the position along the local depth-axis relative to "
+            "the probe origin (see coordinate_reference_point in *_probes.tsv) in micrometers (um). "
+            "When a space-<label> entity is used in the filename, the position relative to the origin of the "
+            "coordinate system along the third axis. Units are specified by MicroephysCoordinateUnits in the "
+            "corresponding *_coordsystem.json file. For 2D electrode localizations (for example, when the "
+            "coordinate system is Pixels), this SHOULD be a column of n/a values."
+        ),
+        title="z",
+        default=numpy.nan,
+    )
+    hemisphere: typing.Literal["L", "R", "n/a"] = pydantic.Field(
+        description="The hemisphere in which the electrode is placed.", title="Hemisphere", default="n/a"
+    )
+    impedance: float = pydantic.Field(
+        description="Impedance of the electrode, units MUST be in kOhm.", title="Impedance", default=numpy.nan
+    )
+    shank_id: str = pydantic.Field(
+        description=(
+            "A unique identifier to specify which shank of the probe the electrode is on. "
+            "This is useful for spike sorting when the electrodes are on a multi-shank probe."
+        ),
+        title="Shank ID",
+        default="n/a",
+    )
+    size: float | None = pydantic.Field(
+        description="Surface area of the electrode, units MUST be in um^2.",
+        title="Size",
+        default=None,
+    )
+    electrode_shape: str | None = pydantic.Field(
+        description="Description of the shape of the electrode (for example, square, circle).",
+        title="Electrode shape",
+        default=None,
+    )
+    material: str | None = pydantic.Field(
+        description="Material of the electrode (for example, Tin, Ag/AgCl, Gold).",
+        title="Material",
+        default=None,
+    )
+    location: str | None = pydantic.Field(
+        description="An indication on the location of the electrode (for example, cortical layer 3, CA1).",
+        title="Location",
+        default=None,
+    )
+    pipette_solution: str | None = pydantic.Field(
+        description="The solution used to fill the pipette.",
+        title="Pipette solution",
+        default=None,
+    )
+    internal_pipette_diameter: float | None = pydantic.Field(
+        description="The internal diameter of the pipette in micrometers.",
+        title="Internal pipette diameter",
+        default=None,
+    )
+    external_pipette_diameter: float | None = pydantic.Field(
+        description="The external diameter of the pipette in micrometers.",
+        title="External pipette diameter",
+        default=None,
+    )
 
     def __eq__(self, other: typing.Any) -> bool:
         if not isinstance(other, Electrode):
@@ -184,9 +269,10 @@ def to_json(self, file_path: str | pathlib.Path) -> None:
         """
         file_path = pathlib.Path(file_path)
 
+        json_content = _build_json_sidecar(models=self.electrodes)
+
+        if "hemisphere" in json_content:
+            json_content["hemisphere"]["Levels"] = {"L": "left", "R": "right"}
+
         with file_path.open(mode="w") as file_stream:
-            json.dump(
-                obj=dict(),  # TODO
-                fp=file_stream,
-                indent=4,
-            )
+            json.dump(obj=json_content, fp=file_stream, indent=4)
diff --git a/src/nwb2bids/bids_models/_model_utils.py b/src/nwb2bids/bids_models/_model_utils.py
new file mode 100644
index 00000000..f5618e05
--- /dev/null
+++ b/src/nwb2bids/bids_models/_model_utils.py
@@ -0,0 +1,35 @@
+import collections
+import typing
+
+import pydantic
+import pydantic_core
+
+
+def _get_present_fields(models: typing.Sequence[pydantic.BaseModel]) -> set[str]:
+    """Return a set of field names that are present or required in the model."""
+    present_non_additional_fields = {
+        field
+        for model in models
+        for field, value in model.model_dump().items()
+        if field in model.model_fields
+        and (
+            value is not None
+            or model.model_fields.get(field, pydantic.fields.FieldInfo()).default is pydantic_core.PydanticUndefined
+        )
+    }
+    return present_non_additional_fields
+
+
+def _build_json_sidecar(models: typing.Sequence[pydantic.BaseModel]) -> dict[str, dict[str, typing.Any]]:
+    """Build a JSON sidecar dictionary from the provided models."""
+    present_non_additional_fields = _get_present_fields(models=models)
+
+    reference_model = list(models)[0]
+    json_content: dict[str, dict[str, typing.Any]] = collections.defaultdict(dict)
+    for field in present_non_additional_fields:
+        if title := getattr(reference_model.model_fields[field], "title"):
+            json_content[field]["LongName"] = title
+        if description := getattr(reference_model.model_fields[field], "description"):
+            json_content[field]["Description"] = description
+
+    return json_content
diff --git a/src/nwb2bids/bids_models/_probes.py b/src/nwb2bids/bids_models/_probes.py
index 639b1a4e..9cfd7bbb 100644
--- a/src/nwb2bids/bids_models/_probes.py
+++ b/src/nwb2bids/bids_models/_probes.py
@@ -1,41 +1,165 @@
 import json
 import pathlib
 import typing
-from typing import Any
 
 import pandas
 import pydantic
 import pynwb
 import typing_extensions
 
+from ._model_utils import _build_json_sidecar
 from ..bids_models._base_metadata_model import BaseMetadataContainerModel, BaseMetadataModel
 from ..notifications import Notification
 
 
 class Probe(BaseMetadataModel):
-    probe_name: str
-    type: str = "n/a"
-    AP: float | None = None
-    ML: float | None = None
-    DV: float | None = None
-    AP_angle: float | None = None
-    ML_angle: float | None = None
-    manufacturer: str | None = None
-    model: str | None = None
-    device_serial_number: str | None = None
-    electrode_count: int | None = None
-    width: float | None = None  # in millimeters
-    height: float | None = None  # in millimeters
-    depth: float | None = None
-    rotation_angle: float | None = None
-    coordinate_reference_point: str | None = None
-    anatomical_reference_point: str | None = None
-    hemisphere: typing.Literal["L", "R"] | None = None
-    associated_brain_region: str | None = None
-    associated_brain_region_id: str | None = None
-    associated_brain_region_quality_type: str | None = None
-    reference_atlas: str | None = None
-    material: str | None = None
+    probe_name: str = pydantic.Field(
+        description="A unique identifier of the probe, can be identical with the device_serial_number.",
+        title="Probe name",
+    )
+    type: str = pydantic.Field(description="The type of the probe.", title="Type", default="n/a")
+    AP: float | None = pydantic.Field(
+        description=(
+            "Probe position along the Anterior-Posterior axis. Positive values are anterior to the reference point."
+        ),
+        title="AP",
+        default=None,
+    )
+    ML: float | None = pydantic.Field(
+        description=(
+            "Probe position along the Medial-Lateral axis. Positive values are to the right (as seen from behind)."
+        ),
+        title="ML",
+        default=None,
+    )
+    DV: float | None = pydantic.Field(
+        description="Probe position along the Dorsal-Ventral axis. Positive values are ventral.",
+        title="DV",
+        default=None,
+    )
+    AP_angle: float | None = pydantic.Field(
+        description=(
+            "Anterior-Posterior rotation angle measured as rotation from the vertical axis in the sagittal plane. "
+            "0° represents vertical along DV axis. Positive values indicate anterior rotation."
+        ),
+        title="AP angle",
+        default=None,
+    )
+    ML_angle: float | None = pydantic.Field(
+        description=(
+            "Medial-Lateral rotation angle measured as rotation from the vertical axis in the coronal plane. "
+            "0° represents vertical along DV axis. Positive values indicate rightward/clockwise rotation "
+            "(as seen from behind)."
+        ),
+        title="ML angle",
+        default=None,
+    )
+    manufacturer: str | None = pydantic.Field(
+        description="Manufacturer of the probes system (for example, 'openephys', 'alphaomega','blackrock').",
+        title="Manufacturer",
+        default=None,
+    )
+    model: str | None = pydantic.Field(
+        description="The model name or number of the probe (for example, Neuropixels 1.0, A1x32-Poly3-5mm-25s-177).",
+        title="Model",
+        default=None,
+    )
+    device_serial_number: str | None = pydantic.Field(
+        description="The serial number of the probe (provided by the manufacturer).",
+        title="Device serial number",
+        default=None,
+    )
+    electrode_count: int | None = pydantic.Field(
+        description="Number of miscellaneous analog electrodes for auxiliary signals (for example, '2').",
+        title="Electrode count",
+        default=None,
+    )
+    width: float | None = pydantic.Field(
+        description=(
+            "Physical width of the probe in mm, for example, '5'. "
+            "This dimension corresponds to the x-axis of the probe's local coordinate frame."
+        ),
+        title="Width",
+        default=None,
+    )
+    height: float | None = pydantic.Field(
+        description=(
+            "Physical height of the probe in mm, for example, '0.3'. "
+            "This dimension should be omitted or set to 0 for one-dimensional (linear) probes. "
+            "This dimension corresponds to the y-axis of the probe's local coordinate frame."
+        ),
+        title="Height",
+        default=None,
+    )
+    depth: float | None = pydantic.Field(
+        description=(
+            "Physical depth of the probe in mm, for example, '0.3'. "
+            "This dimension should be omitted or set to 0 for two-dimensional (shank-type) probes. "
+            "This dimension corresponds to the z-axis of the probe's local coordinate frame."
+        ),
+        title="Depth",
+        default=None,
+    )
+    rotation_angle: float | None = pydantic.Field(
+        description=(
+            "Rotation angle around the probe axis. "
+            "0° when probe features align with the coronal plane. "
+            "Positive rotation is clockwise when viewed from above."
+        ),
+        title="Rotation angle",
+        default=None,
+    )
+    coordinate_reference_point: str | None = pydantic.Field(
+        description=(
+            "Point of the probe that is described by the probe coordinates and on which the yaw, pitch, "
+            "and roll rotations are applied."
+        ),
+        title="Coordinate reference point",
+        default=None,
+    )
+    anatomical_reference_point: str | None = pydantic.Field(
+        description=(
+            "Anatomical reference point for stereotaxic coordinates (for example, Bregma, Lambda). "
+            "If not specified, Bregma is assumed for rodents. MUST be defined for species other than rodents."
+        ),
+        title="Anatomical reference point",
+        default=None,
+    )
+    hemisphere: typing.Literal["L", "R", "n/a"] | None = pydantic.Field(
+        description="Hemisphere in which the probe is placed.", title="Hemisphere", default=None
+    )
+    associated_brain_region: str | None = pydantic.Field(
+        description=(
+            "A textual indication on the location of the probe, preferably species-independent terms as obtained, "
+            "for example from Uberon."
+        ),
+        title="Associated brain region",
+        default=None,
+    )
+    associated_brain_region_id: str | None = pydantic.Field(
+        description=(
+            "An identifier of the associated brain region based on the Uberon ontology for anatomical structures "
+            'in animals, for example "UBERON:0010415"'
+        ),
+        title="Associated brain region ID",
+        default=None,
+    )
+    associated_brain_region_quality_type: str | None = pydantic.Field(
+        description="The method used to identify the associated brain region (estimated).",
+        title="Associated brain region quality type",
+        default=None,
+    )
+    reference_atlas: str | None = pydantic.Field(
+        description=(
+            "Name of reference atlas used for associated brain region identification, "
+            "preferably an ebrains supported atlas."
+        ),
+        title="Reference atlas",
+        default=None,
+    )
+    material: str | None = pydantic.Field(
+        description="A textual description of the base material of the probe.", title="Material", default=None
+    )
 
 
 class ProbeTable(BaseMetadataContainerModel):
@@ -54,7 +178,7 @@ def _check_fields(self) -> None:
             )
             self._internal_notifications.append(notification)
 
-    def model_post_init(self, context: Any, /) -> None:
+    def model_post_init(self, context: typing.Any, /) -> None:
         self._check_fields()
 
     @pydantic.computed_field
@@ -142,13 +266,15 @@ def to_json(self, file_path: str | pathlib.Path) -> None:
         """
         file_path = pathlib.Path(file_path)
 
+        json_content = _build_json_sidecar(models=self.probes)
+
         default_descriptions = {
-            "description": "Probe description from NWB file.",
+            "description": {"Description": "Probe description from NWB file.", "LongName": "Description"}
         }
+        json_content.update(default_descriptions)
+
+        if "hemisphere" in json_content:
+            json_content["hemisphere"]["Levels"] = {"L": "left", "R": "right"}
 
         with file_path.open(mode="w") as file_stream:
-            json.dump(
-                obj={field: desc for field, desc in default_descriptions.items() if hasattr(self, field)},
-                fp=file_stream,
-                indent=4,
-            )
+            json.dump(obj=json_content, fp=file_stream, indent=4)
diff --git a/tests/integration/test_convert_nwb_dataset.py b/tests/integration/test_convert_nwb_dataset.py
index bd6b6c39..5d0d381c 100644
--- a/tests/integration/test_convert_nwb_dataset.py
+++ b/tests/integration/test_convert_nwb_dataset.py
@@ -147,6 +147,24 @@ def test_ecephys_tutorial_convert_nwb_dataset(
     ]
     assert probes_tsv_lines == expected_probe_tsv_lines
 
+    probes_json_file_path = temporary_bids_directory / "sub-001" / "ses-A" / "ecephys" / "sub-001_ses-A_probes.json"
+    probes_json = json.loads(probes_json_file_path.read_text())
+    expected_probes_json = {
+        "description": {"Description": "Probe description from NWB file.", "LongName": "Description"},
+        "manufacturer": {
+            "Description": "Manufacturer of the probes system (for "
+            "example, 'openephys', "
+            "'alphaomega','blackrock').",
+            "LongName": "Manufacturer",
+        },
+        "probe_name": {
+            "Description": "A unique identifier of the probe, can be " "identical with the device_serial_number.",
+            "LongName": "Probe name",
+        },
+        "type": {"Description": "The type of the probe.", "LongName": "Type"},
+    }
+    assert probes_json == expected_probes_json
+
     electrodes_tsv_file_path = (
         temporary_bids_directory / "sub-001" / "ses-A" / "ecephys" / "sub-001_ses-A_electrodes.tsv"
     )
@@ -164,6 +182,82 @@ def test_ecephys_tutorial_convert_nwb_dataset(
     ]
     assert electrodes_tsv_lines == expected_electrodes_tsv_lines
 
+    electrodes_json_file_path = (
+        temporary_bids_directory / "sub-001" / "ses-A" / "ecephys" / "sub-001_ses-A_electrodes.json"
+    )
+    electrodes_json = json.loads(electrodes_json_file_path.read_text())
+    expected_electrodes_json = {
+        "hemisphere": {
+            "Description": "The hemisphere in which the electrode is " "placed.",
+            "Levels": {"L": "left", "R": "right"},
+            "LongName": "Hemisphere",
+        },
+        "impedance": {"Description": "Impedance of the electrode, units MUST be in " "kOhm.", "LongName": "Impedance"},
+        "location": {
+            "Description": "An indication on the location of the electrode " "(for example, cortical layer 3, CA1).",
+            "LongName": "Location",
+        },
+        "name": {"Description": "Name of the electrode contact point.", "LongName": "Electrode name"},
+        "probe_name": {
+            "Description": "A unique identifier of the probe, can be "
+            "identical with the device_serial_number. The "
+            "value MUST match a probe_name entry in the "
+            "corresponding *_probes.tsv file, linking this "
+            "electrode to its associated probe. For "
+            "electrodes not associated with a probe, use "
+            "n/a.",
+            "LongName": "Probe name",
+        },
+        "shank_id": {
+            "Description": "A unique identifier to specify which shank of "
+            "the probe the electrode is on. This is useful "
+            "for spike sorting when the electrodes are on a "
+            "multi-shank probe.",
+            "LongName": "Shank ID",
+        },
+        "x": {
+            "Description": "Recorded position along the x-axis. When no "
+            "space-<label> entity is used in the filename, the "
+            "position along the local width-axis relative to the "
+            "probe origin (see coordinate_reference_point in "
+            "*_probes.tsv) in micrometers (um). When a space-<label> "
+            "entity is used in the filename, the position relative "
+            "to the origin of the coordinate system along the first "
+            "axis. Units are specified by MicroephysCoordinateUnits "
+            "in the corresponding *_coordsystem.json file.",
+            "LongName": "x",
+        },
+        "y": {
+            "Description": "Recorded position along the y-axis. When no "
+            "space-<label> entity is used in the filename, the "
+            "position along the local height-axis relative to the "
+            "probe origin (see coordinate_reference_point in "
+            "*_probes.tsv) in micrometers (um). When a space-<label> "
+            "entity is used in the filename, the position relative "
+            "to the origin of the coordinate system along the second "
+            "axis. Units are specified by MicroephysCoordinateUnits "
+            "in the corresponding *_coordsystem.json file.",
+            "LongName": "y",
+        },
+        "z": {
+            "Description": "Recorded position along the z-axis. For 2D electrode "
+            "localizations, this SHOULD be a column of n/a values. "
+            "When no space-<label> entity is used in the filename, "
+            "the position along the local depth-axis relative to the "
+            "probe origin (see coordinate_reference_point in "
+            "*_probes.tsv) in micrometers (um). When a space-<label> "
+            "entity is used in the filename, the position relative "
+            "to the origin of the coordinate system along the third "
+            "axis. Units are specified by MicroephysCoordinateUnits "
+            "in the corresponding *_coordsystem.json file. For 2D "
+            "electrode localizations (for example, when the "
+            "coordinate system is Pixels), this SHOULD be a column "
+            "of n/a values.",
+            "LongName": "z",
+        },
+    }
+    assert electrodes_json == expected_electrodes_json
+
     channels_tsv_file_path = temporary_bids_directory / "sub-001" / "ses-A" / "ecephys" / "sub-001_ses-A_channels.tsv"
     channels_tsv_lines = channels_tsv_file_path.read_text().splitlines()
     expected_channels_tsv_lines = [
@@ -179,6 +273,42 @@ def test_ecephys_tutorial_convert_nwb_dataset(
     ]
     assert channels_tsv_lines == expected_channels_tsv_lines
 
+    channels_json_file_path = temporary_bids_directory / "sub-001" / "ses-A" / "ecephys" / "sub-001_ses-A_channels.json"
+    channels_json = json.loads(channels_json_file_path.read_text())
+    expected_channels_json = {
+        "electrode_name": {
+            "Description": "Name of the electrode contact point. The "
+            "value MUST match a name entry in the "
+            "corresponding *_electrodes.tsv file, "
+            "linking this channel to its associated "
+            "electrode contact point. For channels not "
+            "associated with an electrode, use n/a.",
+            "LongName": "Electrode name",
+        },
+        "gain": {
+            "Description": "Amplification factor applied from signal detection "
+            "at the electrode to the signal stored in the data "
+            "file. If no gain factor is provided it is assumed to "
+            "be 1.",
+            "LongName": "Gain",
+        },
+        "name": {"Description": "Label of the channel.", "LongName": "Channel name"},
+        "sampling_frequency": {"Description": "Sampling rate of the channel in Hz.", "LongName": "Sampling frequency"},
+        "stream_id": {"Description": "Data stream of the recording the signal.", "LongName": "Stream ID"},
+        "type": {
+            "Description": "Type of channel; MUST use the channel types listed "
+            "below. Note that the type MUST be in upper-case.",
+            "LongName": "Type",
+        },
+        "units": {
+            "Description": "Physical unit of the value represented in this "
+            "channel, for example, V for Volt, or fT/cm for "
+            "femto Tesla per centimeter (see Units).",
+            "LongName": "Units",
+        },
+    }
+    assert channels_json == expected_channels_json
+
 
 def test_ecephys_minimal_convert_nwb_dataset(
     ecephys_minimal_nwbfile_path: pathlib.Path, temporary_bids_directory: pathlib.Path
diff --git a/tests/unit/test_json.py b/tests/unit/test_json.py
new file mode 100644
index 00000000..6816c014
--- /dev/null
+++ b/tests/unit/test_json.py
@@ -0,0 +1,33 @@
+import json
+import pathlib
+
+import nwb2bids
+
+
+def test_probe_json_includes_optional_fields_when_set(tmp_path: pathlib.Path) -> None:
+    """Recommended unit test from review of PR #301."""
+    probe_table = nwb2bids.bids_models.ProbeTable(
+        probes=[
+            nwb2bids.bids_models.Probe(probe_name="ProbeA", manufacturer="openephys", description="test probe"),
+        ],
+        modality="ecephys",
+    )
+
+    json_path = tmp_path / "probes.json"
+    probe_table.to_json(json_path)
+
+    json_content = json.loads(json_path.read_text())
+
+    expected_content = {
+        "description": {"Description": "Probe description from NWB file.", "LongName": "Description"},
+        "manufacturer": {
+            "Description": "Manufacturer of the probes system (for example, 'openephys', 'alphaomega','blackrock').",
+            "LongName": "Manufacturer",
+        },
+        "probe_name": {
+            "Description": "A unique identifier of the probe, can be identical with the device_serial_number.",
+            "LongName": "Probe name",
+        },
+        "type": {"Description": "The type of the probe.", "LongName": "Type"},
+    }
+    assert json_content == expected_content