Database Schema
The synaptic physiology database is provided as sqlite files that can be queried using many relational database tools. Although it is possible to read this dataset using standard SQL queries, we also provide an sqlalchemy model that implements a richer interface to the database. The API reference below is derived from the sqlalchemy model classes, but also doubles as a description of the relational database schema.
Metadata
- class aisynphys.database.schema.Metadata(**kwargs)
Sqlalchemy model for “Metadata” database table.
A single metadata related to the entire database.
- Attributes
- idINTEGER
- metaVARCHAR
Slice
- class aisynphys.database.schema.Slice(**kwargs)
Sqlalchemy model for “Slice” database table.
All brain slices on which an experiment was attempted.
- Attributes
- experimentsrelationship
Reference to experiment.id
- cortical_sitesrelationship
Reference to cortical_site.id
- idINTEGER
- ext_idVARCHAR
Unique external ID for this slice
- acq_timestampFLOAT
Creation timestamp for slice data acquisition folder.
- speciesVARCHAR
human | mouse (from LIMS)
- date_of_birthDATETIME
Date of birth for this specimen
- ageINTEGER
Specimen age (in days) at time of dissection (from LIMS)
- sexVARCHAR
Specimen sex (“M”, “F”, or “unknown”; from LIMS)
- weightVARCHAR
Specimen weight (from LIMS)
- genotypeVARCHAR
Specimen donor genotype (from LIMS)
- orientationVARCHAR
Orientation of the slice plane (eg “sagittal”; from LIMS specimen name)
- surfaceVARCHAR
The surface of the slice exposed during the experiment (eg “left”; from LIMS specimen name)
- hemisphereVARCHAR
The brain hemisphere from which the slice originated. (from LIMS specimen name)
- qualityINTEGER
Experimenter subjective slice quality assessment (0-5)
- slice_timeDATETIME
Time when this specimen was sliced
- slice_conditionsVARCHAR
JSON containing solutions, perfusion, incubation time, etc.
- lims_specimen_nameVARCHAR
Name of LIMS “slice” specimen
- storage_pathVARCHAR
Location of data within server or cache storage
- metaVARCHAR
Experiment
- class aisynphys.database.schema.Experiment(**kwargs)
Sqlalchemy model for “Experiment” database table.
A group of cells patched simultaneously in the same slice.
- Attributes
- slicerelationship
Reference to slice.id
- electrodesrelationship
Reference to electrode.id
- cell_listrelationship
Reference to cell.id
- pair_listrelationship
Reference to pair.id
- sync_recsrelationship
Reference to sync_rec.id
- cortical_sitesrelationship
Reference to cortical_site.id
- idINTEGER
- ext_idVARCHAR
Unique external identifier string for the experiment.
- slice_idINTEGER
ID of the slice used for this experiment
- project_nameVARCHAR
Name of the project to which this experiment belongs.
- dateDATETIME
The date of this experiment
- target_regionVARCHAR
The intended brain region for this experiment
- internalVARCHAR
The name of the internal solution used in this experiment (or “mixed” if more than one solution was used). The solution should be described in the pycsf database.
- acsfVARCHAR
The name of the ACSF solution used in this experiment. The solution should be described in the pycsf database.
- target_temperatureFLOAT
The intended temperature of the experiment (measured temperature per-recording is stored elsewhere)
- rig_nameVARCHAR
Identifier for the rig that generated these results.
- operator_nameVARCHAR
Opertator that generated these results.
- storage_pathVARCHAR
Location of data within server or cache storage.
- ephys_fileVARCHAR
Name of ephys NWB file relative to storage_path.
- acq_timestampFLOAT
Creation timestamp for site data acquisition folder.
- metaVARCHAR
Electrode
- class aisynphys.database.schema.Electrode(**kwargs)
Sqlalchemy model for “Electrode” database table.
Each electrode records a patch attempt, whether or not it resulted in a successful cell recording.
- Attributes
- experimentrelationship
Reference to experiment.id
- cellrelationship
Reference to cell.id
- recordingsrelationship
Reference to recording.id
- test_pulsesrelationship
Reference to test_pulse.id
- idINTEGER
- experiment_idINTEGER
- ext_idVARCHAR
Electrode ID (usually 1-8) referenced in external metadata records
- patch_statusVARCHAR
Status of the patch attempt: no seal, low seal, GOhm seal, tech fail, or no attempt
- start_timeDATETIME
The time when recording began for this electrode.
- stop_timeDATETIME
The time when recording ended for this electrode.
- device_idINTEGER
External identifier for the device attached to this electrode (usually the MIES A/D channel)
- metaVARCHAR
Cell
- class aisynphys.database.schema.Cell(**kwargs)
Sqlalchemy model for “Cell” database table.
Each row represents a single cell in an experiment.
- Attributes
- experimentrelationship
Reference to experiment.id
- electroderelationship
Reference to electrode.id
- intrinsicrelationship
Reference to intrinsic.id
- morphologyrelationship
Reference to morphology.id
- stim_pulsesrelationship
Reference to stim_pulse.id
- cortical_locationrelationship
Reference to cortical_cell_location.id
- patch_seqrelationship
Reference to patch_seq.id
- idINTEGER
- experiment_idINTEGER
- ext_idVARCHAR
Cell ID (usually 1-8) referenced in external metadata records
- electrode_idINTEGER
ID of the electrode used to patch this cell, if any.
- cre_typeVARCHAR
Comma-separated list of cre drivers apparently expressed by this cell
- target_layerVARCHAR
The intended cortical layer for this cell (used as a placeholder until the actual layer call is made)
- positionVARCHAR
3D location of this cell in the arbitrary coordinate system of the experiment
- depthFLOAT
Depth of the cell (in m) from the cut surface of the slice.
- cell_classVARCHAR
Cell class “ex”, “in”, or “mixed” determined by synaptic current, cre type, or morphology. This property makes use of synaptic currents to define cell class; it should _not_ be used when measuring connection probability.
- cell_class_nonsynapticVARCHAR
Cell class “ex”, “in”, or “mixed” determined by cre type or morphology. Unlike cell_class, this property excludes synaptic currents as a determinant so that it can be used in measurements of connectivity.
- metaVARCHAR
Pair
- class aisynphys.database.schema.Pair(**kwargs)
Sqlalchemy model for “Pair” database table.
An ordered pair of cells, possibly connected by a synapse or gap junction.
- Attributes
- experimentrelationship
Reference to experiment.id
- pre_cellrelationship
Reference to cell.id
- post_cellrelationship
Reference to cell.id
- reciprocalrelationship
Reference to pair.id
- pulse_responsesrelationship
Reference to pulse_response.id
- synapserelationship
Reference to synapse.id
- poly_synapserelationship
Reference to poly_synapse.id
- dynamicsrelationship
Reference to dynamics.id
- synapse_predictionrelationship
Reference to synapse_prediction.id
- gap_junctionrelationship
Reference to gap_junction.id
- synapse_modelrelationship
Reference to synapse_model.id
- idINTEGER
- experiment_idINTEGER
- pre_cell_idINTEGER
ID of the presynaptic cell
- post_cell_idINTEGER
ID of the postsynaptic cell
- has_synapseBOOLEAN
Whether a chemical monosynaptic connection was manually detected for this cell pair
- has_polysynapseBOOLEAN
Whether a polysynaptic connection was manually detected for this cell pair
- has_electricalBOOLEAN
Whether an electrical synapse / gap junction was manually detected for this cell pair
- crosstalk_artifactFLOAT
Amplitude of crosstalk artifact measured in current clamp
- n_ex_test_spikesINTEGER
Number of QC-passed spike-responses recorded for this pair at excitatory holding potential
- n_in_test_spikesINTEGER
Number of QC-passed spike-responses recorded for this pair at inhibitory holding potential
- distanceFLOAT
Distance between somas (in m)
- lateral_distanceFLOAT
Distance between somas perpendicular to the pia-wm axis (in m)
- vertical_distanceFLOAT
Distance between somas along the pia-wm axis (in m)
- reciprocal_idINTEGER
ID of the reciprocal to this cell pair (the pair with pre_cell and post_cell swapped)
- metaVARCHAR
Intrinsic
- class aisynphys.database.schema.Intrinsic(**kwargs)
Sqlalchemy model for “Intrinsic” database table.
Describes the intrinsic properties of cells using 1 sec long current steps and chirps.
- Attributes
- cellrelationship
Reference to cell.id
- idINTEGER
- cell_idINTEGER
The ID of the entry in the cell table to which these results apply
- rheobaseFLOAT
Current at rheobase
- fi_slopeFLOAT
Slope of the current-spiking relationship
- input_resistanceFLOAT
Input resistance of the cell (from response peaks, capturing properties of channels at baseline)
- input_resistance_ssFLOAT
(True) steady-state input resistance of the cell
- sagFLOAT
Hyperpolarizing sag ratio (peak/steady-state), measured from ~ -100mV current injection
- tauFLOAT
Membrane time constant
- sag_peak_tFLOAT
Time of peak hyperpolarizing sag.
- sag_depolFLOAT
Depolarizing sag ratio (peak/steady-state), measured from the largest subthreshold depolarizing input
- sag_peak_t_depolFLOAT
Time of peak depolarizing sag.
- ap_upstroke_downstroke_ratioFLOAT
The upstroke-downstroke ratio of the first spike
- ap_widthFLOAT
Spike width
- ap_upstrokeFLOAT
Spike upstroke rate
- ap_downstrokeFLOAT
Spike downstroke rate
- ap_threshold_vFLOAT
Spike threshold voltage
- ap_peak_deltavFLOAT
Spike peak voltage relative to threshold
- ap_fast_trough_deltavFLOAT
AHP / fast trough voltage relative to threshold
- firing_rate_rheoFLOAT
Mean firing rate for rheobase sweep
- latency_rheoFLOAT
First spike latency for rheobase sweep
- firing_rate_40paFLOAT
Mean firing rate for +40pA sweep (relative to rheobase)
- latency_40paFLOAT
First spike latency for +40pA sweep (relative to rheobase)
- adaptation_indexFLOAT
Adaptation index (ratio of consecutive ISIs), averaged across sweeps
- isi_cvFLOAT
Coefficient of variation of ISI distribution, averaged across sweeps
- chirp_peak_freqFLOAT
Frequency at which the chirp response peaks
- chirp_3db_freqFLOAT
Frequency at which the chirp response amplitude is 3 dB below the peak.
- chirp_peak_ratioFLOAT
Ratio of chirp resonance peak amplitude to low-frequency response amplitude
- chirp_peak_impedanceFLOAT
Impedance at chirp resonance peak.
- chirp_sync_freqFLOAT
Frequency at which the chirp phase response equals zero.
- chirp_inductive_phaseFLOAT
Integrated of chirp phase response where phase > 0 (below sync freq).
- isi_adapt_ratioFLOAT
Ratio of ISI on 5th to 1st spike
- upstroke_adapt_ratioFLOAT
Ratio of upstroke on 5th to 1st spike
- downstroke_adapt_ratioFLOAT
Ratio of downstroke on 5th to 1st spike
- width_adapt_ratioFLOAT
Ratio of spike width on 5th to 1st spike
- threshold_v_adapt_ratioFLOAT
Ratio of spike threshold on 5th to 1st spike
- metaVARCHAR
Morphology
- class aisynphys.database.schema.Morphology(**kwargs)
Sqlalchemy model for “Morphology” database table.
Describes morphological properties of cells.
- Attributes
- cellrelationship
Reference to cell.id
- idINTEGER
- cell_idINTEGER
The ID of the cell described by each record
- pyramidalBOOLEAN
Indicates whether the experimenter labeled the cell as pyramidal. This call is based on the presence of a prominent apical dendrite seen in the fluorescent dye fill during experiment. The dendrite_type column is recommended as a more reliable indicator of excitatory morphology.
- qual_morpho_typeVARCHAR
Qualitative desctription of cell morphology
- dendrite_typeVARCHAR
Dendrite type of cell (spiny, aspiny, sparsely spiny) determined from biocytin staining. Generally spiny cells are taken to be excitatory; aspiny or sparsely spiny cells are inhibitory.
- apical_trunc_distanceFLOAT
Measured distance to truncation of apical dendrite
- axon_trunc_distanceFLOAT
Measured distance to truncation of axon
- apical_truncationVARCHAR
Qualitative description of apical dendrite truncation
- axon_truncationVARCHAR
Qualitative description of axon truncation
- axon_originVARCHAR
Origination of axon; soma, dendrite, etc
- metaVARCHAR
SyncRec
- class aisynphys.database.schema.SyncRec(**kwargs)
Sqlalchemy model for “SyncRec” database table.
A synchronous recording represents a “sweep” – multiple recordings that were made simultaneously on different electrodes.
- Attributes
- experimentrelationship
Reference to experiment.id
- recordingsrelationship
Reference to recording.id
- idINTEGER
- experiment_idINTEGER
- ext_idVARCHAR
External ID of the SyncRecording
- temperatureFLOAT
Bath temperature during this recording
- metaVARCHAR
Recording
- class aisynphys.database.schema.Recording(**kwargs)
Sqlalchemy model for “Recording” database table.
A recording represents a single contiguous sweep recorded from a single electrode.
- Attributes
- sync_recrelationship
Reference to sync_rec.id
- electroderelationship
Reference to electrode.id
- patch_clamp_recordingrelationship
Reference to patch_clamp_recording.id
- test_pulsesrelationship
Reference to test_pulse.id
- stim_pulsesrelationship
Reference to stim_pulse.id
- baselinesrelationship
Reference to baseline.id
- idINTEGER
- sync_rec_idINTEGER
References the synchronous recording to which this recording belongs.
- electrode_idINTEGER
Identifies the electrode that generated this recording
- start_timeDATETIME
The clock time at the start of this recording
- sample_rateINTEGER
Sample rate for this recording
- device_nameVARCHAR
Name of the device that generated this recording
- stim_nameVARCHAR
The name of the stimulus protocol used in this recording, if any
- stim_metaVARCHAR
A data structure describing the stimulus protocol
- metaVARCHAR
PatchClampRecording
- class aisynphys.database.schema.PatchClampRecording(**kwargs)
Sqlalchemy model for “PatchClampRecording” database table.
Extra data for recordings made with a patch clamp amplifier
- Attributes
- recordingrelationship
Reference to recording.id
- multi_patch_proberelationship
Reference to multi_patch_probe.id
- nearest_test_pulserelationship
Reference to test_pulse.id
- idINTEGER
- recording_idINTEGER
- clamp_modeVARCHAR
The mode used by the patch clamp amplifier: “ic” or “vc”
- patch_modeVARCHAR
The state of the membrane patch. E.g. ‘whole cell’, ‘cell attached’, ‘loose seal’, ‘bath’, ‘inside out’, ‘outside out’
- baseline_potentialFLOAT
Median steady-state potential (recorded for IC or commanded for VC) during the recording
- baseline_currentFLOAT
Median steady-state current (recorded for VC or commanded for IC) during the recording
- baseline_noise_stdevFLOAT
Noise measured as standard deviation of steady-state parts of the recording
- nearest_test_pulse_idINTEGER
ID of the test pulse that was recorded closest to this recording (and possibly embedded within the recording)
- qc_passBOOLEAN
Indicates whether this recording passes a minimal ephys QC
- access_adj_baseline_potentialFLOAT
Baseline membrane potential estimated by adjusting VC command for access resistance
- metaVARCHAR
MultiPatchProbe
- class aisynphys.database.schema.MultiPatchProbe(**kwargs)
Sqlalchemy model for “MultiPatchProbe” database table.
Extra data for multipatch recordings intended to test synaptic dynamics.
- Attributes
- patch_clamp_recordingrelationship
Reference to patch_clamp_recording.id
- idINTEGER
- patch_clamp_recording_idINTEGER
- induction_frequencyFLOAT
The induction frequency (Hz) of presynaptic pulses
- recovery_delayFLOAT
The recovery delay (s) inserted between presynaptic pulses
- n_spikes_evokedINTEGER
The number of presynaptic spikes evoked
- metaVARCHAR
TestPulse
- class aisynphys.database.schema.TestPulse(**kwargs)
Sqlalchemy model for “TestPulse” database table.
A short, usually hyperpolarizing pulse used to test the resistance of pipette, cell access, or cell membrane.
- Attributes
- electroderelationship
Reference to electrode.id
- recordingrelationship
Reference to recording.id
- idINTEGER
- electrode_idINTEGER
ID of the electrode on which this test pulse was recorded.
- recording_idINTEGER
ID of the recording that contains this test pulse, if any.
- start_indexINTEGER
Index into recording where test pulse begins
- stop_indexINTEGER
Index into recording where test pulse ends
- baseline_currentFLOAT
Pipette current immediately before test pulse
- baseline_potentialFLOAT
Membrane potential immediately before test pulse
- access_resistanceFLOAT
Access resistance estimated from test pulse
- input_resistanceFLOAT
Membrane input resistance estimated from test pulse
- capacitanceFLOAT
Membrane capacitance estimated from test pulse
- time_constantFLOAT
Decay time constant of exponential fit to test pulse
- access_resistance_lowpassFLOAT
median access resistance of nearby test pulses (to filter out artifacts)
- metaVARCHAR
StimPulse
- class aisynphys.database.schema.StimPulse(**kwargs)
Sqlalchemy model for “StimPulse” database table.
A pulse stimulus intended to evoke an action potential
- Attributes
- recordingrelationship
Reference to recording.id
- cellrelationship
Reference to cell.id
- spikesrelationship
Reference to stim_spike.id
- pulse_responserelationship
Reference to pulse_response.id
- dataBLOB
Numpy array of presynaptic recording sampled at 20kHz
- idINTEGER
- recording_idINTEGER
- pulse_numberINTEGER
The ordinal position of this pulse within a train of pulses.
- cell_idINTEGER
Cell that was targeted by this stimulus, if any.
- onset_timeFLOAT
The starting time of the pulse, relative to the beginning of the recording
- amplitudeFLOAT
Amplitude of the presynaptic pulse
- durationFLOAT
Length of the pulse in seconds
- n_spikesINTEGER
Number of spikes evoked by this pulse
- first_spike_timeFLOAT
Time of the first spike evoked by this pulse, measured from the beginning of the recording until the max slope of the spike rising phase.
- data_start_timeFLOAT
Starting time of the data chunk, relative to the beginning of the recording
- positionVARCHAR
3D location of this stimulation in the arbitrary coordinate system of the experiment
- qc_passBOOLEAN
Indicates whether this stimulation passed qc.
- previous_pulse_dtFLOAT
Time elapsed since the last stimulus in the same cell
- metaVARCHAR
StimSpike
- class aisynphys.database.schema.StimSpike(**kwargs)
Sqlalchemy model for “StimSpike” database table.
An action potential evoked by a stimulus pulse. Note that some metrics may be omitted if they could not be determined accurately.
- Attributes
- stim_pulserelationship
Reference to stim_pulse.id
- idINTEGER
- stim_pulse_idINTEGER
- onset_timeFLOAT
The time of the earliest detectable effect of the spike.
- max_slope_timeFLOAT
The time of the max slope of the spike, relative to the beginning of the recording.
- max_slopeFLOAT
Maximum slope of the presynaptic spike
- peak_timeFLOAT
The time of the peak of the spike, relative to the beginning of the recording.
- peak_diffFLOAT
Amplitude of the spike peak, relative to baseline
- peak_valueFLOAT
Absolute value of the spike peak
- metaVARCHAR
PulseResponse
- class aisynphys.database.schema.PulseResponse(**kwargs)
Sqlalchemy model for “PulseResponse” database table.
A chunk of postsynaptic recording taken during a presynaptic pulse stimulus
- Attributes
- stim_pulserelationship
Reference to stim_pulse.id
- recordingrelationship
Reference to recording.id
- pairrelationship
Reference to pair.id
- baselinerelationship
Reference to baseline.id
- pulse_response_fitrelationship
Reference to pulse_response_fit.id
- pulse_response_strengthrelationship
Reference to pulse_response_strength.id
- dataBLOB
numpy array of response data sampled at 20kHz
- idINTEGER
- recording_idINTEGER
The full recording from which this pulse was extracted
- stim_pulse_idINTEGER
The presynaptic pulse
- pair_idINTEGER
The pre-post cell pair involved in this pulse response
- baseline_idINTEGER
A random baseline snippet matched from the same recording.
- data_start_timeFLOAT
Starting time of this chunk of the recording in seconds, relative to the beginning of the recording
- ex_qc_passBOOLEAN
Indicates whether this recording snippet passes QC for excitatory synapse probing
- in_qc_passBOOLEAN
Indicates whether this recording snippet passes QC for inhibitory synapse probing
- metaVARCHAR
Baseline
- class aisynphys.database.schema.Baseline(**kwargs)
Sqlalchemy model for “Baseline” database table.
A snippet of baseline data used for comparison to pulse_response records
- Attributes
- recordingrelationship
Reference to recording.id
- pulse_responsesrelationship
Reference to pulse_response.id
- dataBLOB
numpy array of baseline data sampled at 20kHz
- idINTEGER
- recording_idINTEGER
The recording from which this baseline snippet was extracted.
- data_start_timeFLOAT
Starting time of this chunk of the recording in seconds, relative to the beginning of the recording
- modeFLOAT
most common value in the baseline snippet
- ex_qc_passBOOLEAN
Indicates whether this recording snippet passes QC for excitatory synapse probing
- in_qc_passBOOLEAN
Indicates whether this recording snippet passes QC for inhibitory synapse probing
- metaVARCHAR
Synapse
- class aisynphys.database.schema.Synapse(**kwargs)
Sqlalchemy model for “Synapse” database table.
Chemical synapse properties
- Attributes
- pairrelationship
Reference to pair.id
- avg_response_fitsrelationship
Reference to avg_response_fit.id
- resting_state_fitrelationship
Reference to resting_state_fit.id
- conductancerelationship
Reference to conductance.id
- idINTEGER
- pair_idINTEGER
The ID of the entry in the pair table to which these results apply
- synapse_typeVARCHAR
“ex” or “in” indicating whether the synapse is excitatory or inhibitory
- latencyFLOAT
Latency in seconds from spike max slope until synaptic response onset.
- psp_amplitudeFLOAT
Amplitude of resting-state PSPs in Volts.
- psp_rise_timeFLOAT
Rise time in seconds measured from averaged PSPs.
- psp_decay_tauFLOAT
decay time constant in seconds measured from averaged PSPs.
- psc_amplitudeFLOAT
Amplitude of resting-state PSCs in Amperes.
- psc_rise_timeFLOAT
Rise time in seconds measured from averaged PSCs.
- psc_decay_tauFLOAT
decay time constant in seconds measured from averaged PSCs.
- metaVARCHAR
AvgResponseFit
- class aisynphys.database.schema.AvgResponseFit(**kwargs)
Sqlalchemy model for “AvgResponseFit” database table.
Fit to average post synaptic response for a given pair. Each pair may have fits for VC and IC recordings, held at -70 and -55 mV.
- Attributes
- synapserelationship
Reference to synapse.id
- poly_synapserelationship
Reference to poly_synapse.id
- avg_dataBLOB
Averaged PSP/PSC that was fit.
- idINTEGER
- synapse_idINTEGER
The ID of the entry in the synapse table to which these results apply
- poly_synapse_idINTEGER
The ID of the entry in the poly_synapse table to which these results apply
- clamp_modeVARCHAR
The clamp mode “ic” or “vc”
- holdingFLOAT
The holding potential -70 or -55
- laser_power_commandFLOAT
The pockel cell command value for the 2p laser
- fit_xoffsetFLOAT
Fit time from max slope of the presynaptic spike until onset of the synaptic response (seconds)
- fit_yoffsetFLOAT
Fit constant y-offset (amps or volts)
- fit_ampFLOAT
Fit synaptic response amplitude (amps or volts)
- fit_rise_timeFLOAT
Fit rise time (seconds) from response onset until peak
- fit_rise_powerFLOAT
Fit rise exponent (usually fixed at 2)
- fit_decay_tauFLOAT
Fit exponential decay time constant (seconds)
- fit_exp_ampFLOAT
Fit baseline exponental amplitude (amps or volts)
- fit_exp_tauFLOAT
Fit baseline exponental decay time constant (seconds)
- nrmseFLOAT
Normalized RMS error of the fit residual
- initial_xoffsetFLOAT
Initial latency supplied to fitting algorithm
- manual_qc_passBOOLEAN
If true, this fit passes manual verification QC
- avg_data_start_timeFLOAT
Starting time of avg_data, relative to the presynaptic spike
- n_averaged_responsesINTEGER
Number of postsynaptic responses that were averaged in avg_data
- avg_baseline_noiseFLOAT
Standard deviation of avg_data before the presynaptic stimulus
- metaVARCHAR
PolySynapse
- class aisynphys.database.schema.PolySynapse(**kwargs)
Sqlalchemy model for “PolySynapse” database table.
Chemical properties of polysnaptic events
- Attributes
- pairrelationship
Reference to pair.id
- avg_response_fitsrelationship
Reference to avg_response_fit.id
- resting_state_fitrelationship
Reference to resting_state_fit.id
- idINTEGER
- pair_idINTEGER
The ID of the entry in the pair table to which these results apply
- synapse_typeVARCHAR
“ex” or “in” indicating whether the synapse is excitatory or inhibitory
- latencyFLOAT
Latency in seconds from spike max slope until synaptic response onset.
- psp_amplitudeFLOAT
Amplitude of resting-state PSPs in Volts.
- psp_rise_timeFLOAT
Rise time in seconds measured from averaged PSPs.
- psp_decay_tauFLOAT
decay time constant in seconds measured from averaged PSPs.
- psc_amplitudeFLOAT
Amplitude of resting-state PSCs in Amperes.
- psc_rise_timeFLOAT
Rise time in seconds measured from averaged PSCs.
- psc_decay_tauFLOAT
decay time constant in seconds measured from averaged PSCs.
- metaVARCHAR
PulseResponseFit
- class aisynphys.database.schema.PulseResponseFit(**kwargs)
Sqlalchemy model for “PulseResponseFit” database table.
Curve fits to individual synaptic responses.
- Attributes
- pulse_responserelationship
Reference to pulse_response.id
- idINTEGER
- pulse_response_idINTEGER
- fit_ampFLOAT
Fit amplitude of the response to this stimulus
- fit_latencyFLOAT
Fit latency of the response to this stimulus
- fit_yoffsetFLOAT
Fit y offset of the response to this stimulus
- fit_rise_timeFLOAT
Fit rise time of the response to this stimulus
- fit_decay_tauFLOAT
Fit decay tau of the response to this stimulus
- fit_exp_ampFLOAT
Fit exponential amplitude of the baseline before this stimulus
- fit_nrmseFLOAT
Normalized RMS error of the fit
- baseline_fit_ampFLOAT
Fit amplitude of the baseline before the stimulus
- baseline_fit_latencyFLOAT
Fit latency of the baseline before the stimulus
- baseline_fit_yoffsetFLOAT
Fit y offset of the baseline before the stimulus
- baseline_fit_rise_timeFLOAT
Fit rise time of the baseline before the stimulus
- baseline_fit_decay_tauFLOAT
Fit decay tau of the baseline before the stimulus
- baseline_fit_exp_ampFLOAT
Fit exponential amplitude of the baseline before this stimulus
- baseline_fit_nrmseFLOAT
Normalized RMS error of the fit
- dec_fit_ampFLOAT
Fit amplitude of the deconvolved response to this stimulus
- dec_fit_reconv_ampFLOAT
Fit amplitude of the deconvolved response to this stimulus, reconvolved to physiological units
- dec_fit_latencyFLOAT
Fit latency of the deconvolved response to this stimulus
- dec_fit_yoffsetFLOAT
Fit y offset of the deconvolved response to this stimulus
- dec_fit_rise_timeFLOAT
Fit rise time of the deconvolved response to this stimulus
- dec_fit_decay_tauFLOAT
Fit decay tau of the deconvolved response to this stimulus
- dec_fit_nrmseFLOAT
Normalized RMS error of the fit
- baseline_dec_fit_ampFLOAT
Fit amplitude of the deconvolved baseline before the stimulus
- baseline_dec_fit_reconv_ampFLOAT
Fit amplitude of the deconvolved baseline before this stimulus, reconvolved to physiological units
- baseline_dec_fit_latencyFLOAT
Fit latency of the deconvolved baseline before the stimulus
- baseline_dec_fit_yoffsetFLOAT
Fit y offset of the deconvolved baseline before the stimulus
- baseline_dec_fit_rise_timeFLOAT
Fit rise time of the deconvolved baseline before the stimulus
- baseline_dec_fit_decay_tauFLOAT
Fit decay tau of the deconvolved baseline before the stimulus
- baseline_dec_fit_nrmseFLOAT
Normalized RMS error of the fit
- metaVARCHAR
PulseResponseStrength
- class aisynphys.database.schema.PulseResponseStrength(**kwargs)
Sqlalchemy model for “PulseResponseStrength” database table.
Measurements of membrane potential or current deflection following each evoked presynaptic spike.
- Attributes
- pulse_responserelationship
Reference to pulse_response.id
- baselinerelationship
Reference to baseline.id
- idINTEGER
- pulse_response_idINTEGER
- pos_ampFLOAT
max-median offset from baseline to pulse response window
- neg_ampFLOAT
min-median offset from baseline to pulse response window
- pos_dec_ampFLOAT
max-median offset from baseline to pulse response window from devonvolved trace
- neg_dec_ampFLOAT
min-median offset from baseline to pulse response window from deconvolved trace
- pos_dec_latencyFLOAT
duration (seconds) from presynaptic spike max dv/dt until the sample measured in pos_dec_amp
- neg_dec_latencyFLOAT
duration (seconds) from presynaptic spike max dv/dt until the sample measured in neg_dec_amp
- crosstalkFLOAT
trace difference immediately before and after onset of presynaptic stimulus pulse
- baseline_idINTEGER
- baseline_pos_ampFLOAT
max-median offset from baseline to pulse response window
- baseline_neg_ampFLOAT
min-median offset from baseline to pulse response window
- baseline_pos_dec_ampFLOAT
max-median offset from baseline to pulse response window from devonvolved trace
- baseline_neg_dec_ampFLOAT
min-median offset from baseline to pulse response window from deconvolved trace
- baseline_pos_dec_latencyFLOAT
duration (seconds) from presynaptic spike max dv/dt until the sample measured in pos_dec_amp
- baseline_neg_dec_latencyFLOAT
duration (seconds) from presynaptic spike max dv/dt until the sample measured in neg_dec_amp
- baseline_crosstalkFLOAT
trace difference immediately before and after onset of presynaptic stimulus pulse
- metaVARCHAR
Dynamics
- class aisynphys.database.schema.Dynamics(**kwargs)
Sqlalchemy model for “Dynamics” database table.
Describes short term dynamics of synaptic connections.
- Attributes
- pairrelationship
Reference to pair.id
- stp_all_stimuliVARCHAR
list of initial, induction, and recovery measurements for all stimuli presented
- idINTEGER
- pair_idINTEGER
The ID of the cell pair described by each record
- qc_passBOOLEAN
Indicates whether dynamics records pass quality control
- n_source_eventsINTEGER
Number of qc-passed pulse response amplitudes from which dynamics metrics were generated
- paired_pulse_ratio_50hzFLOAT
The median ratio of 2nd / 1st pulse amplitudes for 50Hz pulse trains.
- stp_initial_50hzFLOAT
The median relative change from 1st to 2nd pulse for 50Hz pulse trains
- stp_initial_50hz_nFLOAT
Number of samples represented in stp_initial_50Hz
- stp_initial_50hz_stdFLOAT
Standard deviation of samples represented in stp_initial_50Hz
- stp_induction_50hzFLOAT
The median relative change from 1st to 6th-8th pulses for 50Hz pulse trains
- stp_induction_50hz_nFLOAT
Number of samples represented in stp_induction_50Hz
- stp_induction_50hz_stdFLOAT
Standard deviation of samples represented in stp_induction_50Hz
- stp_recovery_250msFLOAT
The median relative change from 1st-4th to 9th-12th pulses for pulse trains with a 250 ms recovery period
- stp_recovery_250ms_nFLOAT
Number of samples represented in stp_recovery_250ms
- stp_recovery_250ms_stdFLOAT
Standard deviation of samples represented in stp_recovery_250ms
- stp_recovery_single_250msFLOAT
The median relative change from 1st to 9th pulses for pulse trains with a 250 ms recovery period
- stp_recovery_single_250ms_nFLOAT
Number of samples represented in stp_recovery_single_250ms
- stp_recovery_single_250ms_stdFLOAT
Standard deviation of samples represented in stp_recovery_single_250ms
- pulse_amp_90th_percentileFLOAT
The 90th-percentile largest pulse amplitude, used to normalize change values in this table
- noise_amp_90th_percentileFLOAT
The 90th-percentile largest amplitude measured from background noise, used for comparison to pulse_amp_90th_percentile
- pulse_amp_first_50hzFLOAT
Median amplitude of first pulse on 50 hz trains
- pulse_amp_first_50hz_nFLOAT
Number of samples represented in pulse_amp_first_50hz
- pulse_amp_first_50hz_stdFLOAT
Standard deviation of samples represented in pulse_amp_stp_initial_50hz
- pulse_amp_stp_initial_50hzFLOAT
Median amplitude of second pulse on 50 hz trains
- pulse_amp_stp_initial_50hz_nFLOAT
Number of samples represented in pulse_amp_stp_initial_50hz
- pulse_amp_stp_initial_50hz_stdFLOAT
Standard deviation of samples represented in pulse_amp_stp_initial_50hz
- pulse_amp_stp_induction_50hzFLOAT
Median amplitude of 6th-8th pulses on 50 hz trains
- pulse_amp_stp_induction_50hz_nFLOAT
Number of samples represented in pulse_amp_stp_induction_50hz
- pulse_amp_stp_induction_50hz_stdFLOAT
Standard deviation of samples represented in pulse_amp_stp_induction_50hz
- pulse_amp_stp_recovery_250msFLOAT
Median amplitude of 9th-12th pulses on 50 hz trains
- pulse_amp_stp_recovery_250ms_nFLOAT
Number of samples represented in pulse_amp_stp_recovery_250ms
- pulse_amp_stp_recovery_250ms_stdFLOAT
Standard deviation of samples represented in pulse_amp_stp_recovery_250ms
- pulse_amp_stp_recovery_single_250msFLOAT
Median amplitude of 9th pulse on 50 hz trains
- pulse_amp_stp_recovery_single_250ms_nFLOAT
Number of samples represented in pulse_amp_stp_recovery_single_250ms
- pulse_amp_stp_recovery_single_250ms_stdFLOAT
Standard deviation of samples represented in pulse_amp_stp_recovery_single_250ms
- noise_stdFLOAT
Standard deviation of PSP amplitudes measured from background noise
- variability_resting_stateFLOAT
Variability of PSP amplitudes only from events with no preceding spikes for at least 8 seconds, corrected for background noise.
- variability_second_pulse_50hzFLOAT
Variability of PSP amplitudes in 2nd pulses of 50Hz trains
- variability_stp_induced_state_50hzFLOAT
Variability of PSP amplitudes in 5th-8th pulses of 50Hz trains
- variability_change_initial_50hzFLOAT
Difference between variability of 1st and 2nd pulses in 50Hz trains, corrected for background noise.
- variability_change_induction_50hzFLOAT
Difference between variability of 1st and 5th-8th pulses in 50Hz trains, corrected for background noise.
- paired_event_correlation_1_2_rFLOAT
Pearson correlation coefficient for amplitudes of 1st:2nd pulses in 50Hz trains.
- paired_event_correlation_1_2_pFLOAT
Pearson correlation p-value related to paired_event_correlation_1_2_r.
- paired_event_correlation_2_4_rFLOAT
Pearson correlation coefficient for amplitudes of 1st:2nd pulses in 50Hz trains.
- paired_event_correlation_2_4_pFLOAT
Pearson correlation p-value related to paired_event_correlation_1_2_r.
- paired_event_correlation_4_8_rFLOAT
Pearson correlation coefficient for amplitudes of 1st:2nd pulses in 50Hz trains.
- paired_event_correlation_4_8_pFLOAT
Pearson correlation p-value related to paired_event_correlation_1_2_r.
- metaVARCHAR
SynapsePrediction
- class aisynphys.database.schema.SynapsePrediction(**kwargs)
Sqlalchemy model for “SynapsePrediction” database table.
Unbiased metrics used for automated synapse detection.
- Attributes
- pairrelationship
Reference to pair.id
- idINTEGER
- pair_idINTEGER
The ID of the entry in the pair table to which these results apply
- synapse_typeVARCHAR
String “ex” or “in”, indicating whether this analysis chose to treat the pair as excitatory or inhibitory
- ic_n_samplesINTEGER
Number of samples (pulse responses) that were pooled from current clamp recordings
- ic_crosstalk_meanFLOAT
- ic_base_crosstalk_meanFLOAT
- ic_amp_meanFLOAT
- ic_amp_stdevFLOAT
- ic_base_amp_meanFLOAT
- ic_base_amp_stdevFLOAT
- ic_amp_ttestFLOAT
- ic_amp_ks2sampFLOAT
- ic_deconv_amp_meanFLOAT
- ic_deconv_amp_stdevFLOAT
- ic_base_deconv_amp_meanFLOAT
- ic_base_deconv_amp_stdevFLOAT
- ic_deconv_amp_ttestFLOAT
- ic_deconv_amp_ks2sampFLOAT
- ic_latency_meanFLOAT
- ic_latency_stdevFLOAT
- ic_base_latency_meanFLOAT
- ic_base_latency_stdevFLOAT
- ic_latency_ttestFLOAT
- ic_latency_ks2sampFLOAT
- vc_n_samplesINTEGER
- vc_crosstalk_meanFLOAT
- vc_base_crosstalk_meanFLOAT
- vc_amp_meanFLOAT
- vc_amp_stdevFLOAT
- vc_base_amp_meanFLOAT
- vc_base_amp_stdevFLOAT
- vc_amp_ttestFLOAT
- vc_amp_ks2sampFLOAT
- vc_deconv_amp_meanFLOAT
- vc_deconv_amp_stdevFLOAT
- vc_base_deconv_amp_meanFLOAT
- vc_base_deconv_amp_stdevFLOAT
- vc_deconv_amp_ttestFLOAT
- vc_deconv_amp_ks2sampFLOAT
- vc_latency_meanFLOAT
- vc_latency_stdevFLOAT
- vc_base_latency_meanFLOAT
- vc_base_latency_stdevFLOAT
- vc_latency_ttestFLOAT
- vc_latency_ks2sampFLOAT
- ic_average_responseBLOB
- ic_average_response_t0FLOAT
- ic_average_base_stdevFLOAT
- vc_average_responseBLOB
- vc_average_response_t0FLOAT
- vc_average_base_stdevFLOAT
- ic_fit_ampFLOAT
- ic_fit_xoffsetFLOAT
- ic_fit_yoffsetFLOAT
- ic_fit_rise_timeFLOAT
- ic_fit_rise_powerFLOAT
- ic_fit_decay_tauFLOAT
- ic_fit_exp_ampFLOAT
- ic_fit_exp_tauFLOAT
- ic_fit_nrmseFLOAT
- vc_fit_ampFLOAT
- vc_fit_xoffsetFLOAT
- vc_fit_yoffsetFLOAT
- vc_fit_rise_timeFLOAT
- vc_fit_rise_powerFLOAT
- vc_fit_decay_tauFLOAT
- vc_fit_exp_ampFLOAT
- vc_fit_exp_tauFLOAT
- vc_fit_nrmseFLOAT
- metaVARCHAR
RestingStateFit
- class aisynphys.database.schema.RestingStateFit(**kwargs)
Sqlalchemy model for “RestingStateFit” database table.
Contains curve fits to averages of “resting state” synaptic responses.
- Attributes
- synapserelationship
Reference to synapse.id
- poly_synapserelationship
Reference to poly_synapse.id
- idINTEGER
- synapse_idINTEGER
The ID of the entry in the synapse table to which these results apply
- poly_synapse_idINTEGER
The ID of the entry in the poly_synapse table to which these results apply
- ic_ampFLOAT
fit amplitude of current clamp average first pulses
- ic_latencyFLOAT
fit time elapsed since the time of presynaptic spike (max dv/dt) of current clamp data
- ic_rise_timeFLOAT
fit rise time of psp of current clamp data
- ic_decay_tauFLOAT
fit decay of psp of current clamp data
- ic_exp_ampFLOAT
fit amplitude of exponential baseline
- ic_exp_tauFLOAT
fit tau of exponential baseline
- ic_avg_dataBLOB
array of the data voltage waveform used in fitting
- ic_avg_data_start_timeFLOAT
time value of the first sample in ic_avg_data, relative to the presynaptic spike
- ic_pulse_idsBLOB
data base pulse ids included in the current clamp fit
- ic_nrmseFLOAT
error of fit of current clamp fit
- vc_ampFLOAT
fit amplitude of voltage clamp average first pulses
- vc_latencyFLOAT
fit time elapsed since the time of presynaptic spike (max dv/dt) of voltage clamp data
- vc_rise_timeFLOAT
fit rise time of psp measured in voltage clamp
- vc_decay_tauFLOAT
fit decay of psp measured in voltage clamp
- vc_exp_ampFLOAT
fit amplitude of exponential baseline
- vc_exp_tauFLOAT
fit tau of exponential baseline
- vc_avg_dataBLOB
array of the data current waveform used in fitting
- vc_avg_data_start_timeFLOAT
time value of the first sample in vc_avg_data, relative to the presynaptic spike
- vc_pulse_idsBLOB
data base pulse ids included in the voltage clamp fit
- vc_nrmseFLOAT
error of fit of voltage clamp fit
- metaVARCHAR
GapJunction
- class aisynphys.database.schema.GapJunction(**kwargs)
Sqlalchemy model for “GapJunction” database table.
Describes the presence of gap junction.
- Attributes
- pairrelationship
Reference to pair.id
- idINTEGER
- pair_idINTEGER
The ID of the entry in the pair table to which these results apply
- corr_coeff_pulseFLOAT
The Pearson correlation coefficient of pre- and post-synaptic long pulse
- corr_coeff_noiseFLOAT
The Pearson correlation coefficient of pre- and post-synaptic background
- p_val_pulseFLOAT
The Pearson p-value of pre- and post-synaptic long pulse
- p_val_noiseFLOAT
The Pearson p-value of pre- and post-synaptic background
- coupling_coeff_pulseFLOAT
The coupling coefficient of pre- and post-synaptic long pulse
- coupling_coeff_noiseFLOAT
The coupling coefficient of pre- and post-synaptic background
- junctional_conductanceFLOAT
The junctional conductance of pre- and post-synaptic long pulse
- metaVARCHAR
CorticalCellLocation
- class aisynphys.database.schema.CorticalCellLocation(**kwargs)
Sqlalchemy model for “CorticalCellLocation” database table.
Each row holds location information for a single cortical cell.
- Attributes
- cellrelationship
Reference to cell.id
- cortical_siterelationship
Reference to cortical_site.id
- idINTEGER
- cell_idINTEGER
ID of the cell these locations apply to.
- cortical_site_idINTEGER
ID of the site location measurements fit within.
- cortical_layerVARCHAR
Cortical layer of cell defined by layer drawings (after trimming, not identical to that in LIMS)
- distance_to_piaFLOAT
The distance from the cell to the pial surface in m.
- distance_to_wmFLOAT
The distance from the cell to the white matter in m.
- fractional_depthFLOAT
The cortical depth of the cell where pia is 0 and wm is 1.
- layer_depthFLOAT
Absolute depth within the layer in m.
- layer_thicknessFLOAT
Local thickness of layer in m.
- fractional_layer_depthFLOAT
Fractional depth within the cells layer.
- positionVARCHAR
2D array, position of cell in slice image coordinates (in m)
- metaVARCHAR
CorticalSite
- class aisynphys.database.schema.CorticalSite(**kwargs)
Sqlalchemy model for “CorticalSite” database table.
Each row holds measurements about one cortical site in a slice.
- Attributes
- slicerelationship
Reference to slice.id
- cell_locationsrelationship
Reference to cortical_cell_location.id
- experimentrelationship
Reference to experiment.id
- idINTEGER
- slice_idINTEGER
ID of the slice this site belongs to.
- experiment_idINTEGER
ID to the experiment this site is part of
- pia_to_wm_distanceFLOAT
The distance (in m) from the pia to the white matter.
- pia_positionVARCHAR
3D location where the pia was marked in the arbitrary coordinate system of the experiment
- wm_positionVARCHAR
3D location where the wm was marked in the arbitrary coordinate system of the experiment
- layer_boundariesVARCHAR
Dictionary with fractional layer boundaries appropriate for the site.
- brain_regionVARCHAR
The name of the brain region for the site.
- metaVARCHAR
PatchSeq
- class aisynphys.database.schema.PatchSeq(**kwargs)
Sqlalchemy model for “PatchSeq” database table.
Describes transcriptomic data of a cell obtained from patch_seq experiments
- Attributes
- cellrelationship
Reference to cell.id
- idINTEGER
- cell_idINTEGER
The ID of the cell described by each record
- tube_idVARCHAR
Patched Cell Container ID used for RNA analysis
- nucleusVARCHAR
Whether the nucleus was recovered from the cell, +, -, ?
- resealBOOLEAN
Was there a giga-reseal during nucleus extraction
- patchseq_hashVARCHAR
Hash of patchseq results from amplification and mapping used for updating
- result_baVARCHAR
Pass/Fail
- area_400_10000bpFLOAT
Area (0-1) of amplified content in the 400-10,000 bp range which is an indication of intact RNA
- picogreen_yieldFLOAT
(pg/ul)
- cluster_detailVARCHAR
Detailed name of last mapped cluster, for class-level nodes this a descriptive name
- cluster_labelVARCHAR
Label of last mapped cluster, numerical for class-level nodes
- scoreFLOAT
Mapping score from 0-1
- res_indexFLOAT
Resolution of the last mapped cluster from 0-1 with 1 being the terminal leaf
- top_leafVARCHAR
- top_leaf_scoreFLOAT
Confidence of top_leaf mapping (0-1)
- broad_class_labelVARCHAR
Presumed class designation; assinged to all cells regardless of mapping depth
- subclass_labelVARCHAR
Presumed subclass designation; assigned to all cells regardless of mapping depth
- quality_scoreFLOAT
- norm_marker_sumFLOAT
- seurat_clusterVARCHAR
Mapped cluster based on Seurat method
- seurat_scoreFLOAT
Mapping score of seurat_cluster (0-1)
- tree_first_clusterVARCHAR
First mapping cluster based on Tree method
- tree_first_btFLOAT
Mapping score of first cluster (0-1)
- tree_first_klFLOAT
Divergence of mapping score to FACS data
- tree_first_corFLOAT
Correlation of mapping score to FACS data
- tree_second_clusterVARCHAR
Second mapping cluster based on Tree method
- tree_second_btFLOAT
Mapping score of second cluster (0-1)
- tree_second_klFLOAT
Divergence of mapping score to FACS data
- tree_second_corFLOAT
Correlation of mapping score to FACS data
- tree_third_clusterVARCHAR
Third mapping cluster based on Tree method
- tree_third_btFLOAT
Mapping score of third cluster (0-1)
- tree_callVARCHAR
Tree mapping
- genes_detectedINTEGER
Number of genes detected
- t_typeVARCHAR
Transcriptomic type = tree_first_cluster if tree_call in [Core, I1]
- last_mapVARCHAR
mapping from the last batch run
- last_scoreVARCHAR
mapping score from the last batch run
- mapped_subclassVARCHAR
Subclass that this cell mapped to
- batchVARCHAR
Shiny batch number, used for tracking updates
- metaVARCHAR
SynapseModel
- class aisynphys.database.schema.SynapseModel(**kwargs)
Sqlalchemy model for “SynapseModel” database table.
Summary of stochastic model outputs per synapse
- Attributes
- pairrelationship
Reference to pair.id
- parameter_spaceVARCHAR
Describes the parameter space searched by the model
- marginal_distributionsVARCHAR
Contains marginal distributions for all model parameters
- confidence_intervalsVARCHAR
Contains confidence intervals for all model parameters
- ml_stp_all_stimuliVARCHAR
list of initial, induction, and recovery measurements for all stimuli presented
- idINTEGER
- pair_idINTEGER
The ID of the cell pair described by each record
- n_source_eventsINTEGER
Number of qc-passed pulse response amplitudes used to fit the model
- sparse_pca_vectorBLOB
Sparse PCA vector describing model output over entire parameter space
- max_likelihoodFLOAT
The maximum model likelihood value
- ml_n_release_sitesFLOAT
Maximum likelihood value for n_release_sites
- ml_base_release_probabilityFLOAT
Maximum likelihood value for base_release_probability
- ml_mini_amplitudeFLOAT
Maximum likelihood value for mini_amplitude
- ml_mini_amplitude_cvFLOAT
Maximum likelihood value for mini_amplitude_cv
- ml_depression_amountFLOAT
Maximum likelihood value for depression_amount
- ml_depression_tauFLOAT
Maximum likelihood value for depression_tau
- ml_facilitation_amountFLOAT
Maximum likelihood value for facilitation_amount
- ml_facilitation_tauFLOAT
Maximum likelihood value for facilitation_tau
- ml_measurement_stdevFLOAT
Maximum likelihood value for measurement_stdev
- ml_strengthFLOAT
maximum likelihood value of n_release_sites * base_release_probability * mini_amplitude
- ml_strength_ciVARCHAR
confidence interval for ml_strength
- ml_quanta_per_spikeFLOAT
maximum likelihood value of n_release_sites * base_release_probability
- ml_quanta_per_spike_ciVARCHAR
confidence interval for ml_quanta_per_spike
- ml_sites_pr_ratioFLOAT
maximum likelihood ratio of n_release_sites : base_release_probability
- ml_sites_pr_ratio_ciVARCHAR
confidence interval for ml_sites_pr_ratio
- ml_release_dependence_ratioFLOAT
ratio of maximum likelihood in release-dependent vs release-independent portions of the parameter space
- ml_paired_pulse_ratio_50hzFLOAT
The median ratio of 2nd / 1st pulse amplitudes for 50Hz pulse trains.
- ml_stp_initial_50hzFLOAT
The median relative change from 1st to 2nd pulse for 50Hz pulse trains
- ml_stp_initial_50hz_nFLOAT
Number of samples represented in stp_initial_50Hz
- ml_stp_initial_50hz_stdFLOAT
Standard deviation of samples represented in stp_initial_50Hz
- ml_stp_induction_50hzFLOAT
The median relative change from 1st to 5th-8th pulses for 50Hz pulse trains
- ml_stp_induction_50hz_nFLOAT
Number of samples represented in stp_induction_50Hz
- ml_stp_induction_50hz_stdFLOAT
Standard deviation of samples represented in stp_induction_50Hz
- ml_stp_recovery_250msFLOAT
The median relative change from 1st-4th to 9th-12th pulses for pulse trains with a 250 ms recovery period
- ml_stp_recovery_250ms_nFLOAT
Number of samples represented in stp_recovery_250ms
- ml_stp_recovery_250ms_stdFLOAT
Standard deviation of samples represented in stp_recovery_250ms
- ml_stp_recovery_single_250msFLOAT
The median relative change from 1st to 9th pulses for pulse trains with a 250 ms recovery period
- ml_stp_recovery_single_250ms_nFLOAT
Number of samples represented in stp_recovery_single_250ms
- ml_stp_recovery_single_250ms_stdFLOAT
Standard deviation of samples represented in stp_recovery_single_250ms
- ml_pulse_amp_90th_percentileFLOAT
The 90th-percentile largest pulse amplitude, used to normalize change values in this table
- ml_noise_amp_90th_percentileFLOAT
The 90th-percentile largest amplitude measured from background noise, used for comparison to pulse_amp_90th_percentile
- ml_noise_stdFLOAT
Standard deviation of PSP amplitudes measured from background noise
- ml_variability_resting_stateFLOAT
Variability of PSP amplitudes only from events with no preceding spikes for at least 8 seconds, corrected for background noise.
- ml_variability_second_pulse_50hzFLOAT
Variability of PSP amplitudes in 2nd pulses of 50Hz trains
- ml_variability_stp_induced_state_50hzFLOAT
Variability of PSP amplitudes in 5th-8th pulses of 50Hz trains
- ml_variability_change_initial_50hzFLOAT
Difference between variability of 1st and 2nd pulses in 50Hz trains, corrected for background noise.
- ml_variability_change_induction_50hzFLOAT
Difference between variability of 1st and 5th-8th pulses in 50Hz trains, corrected for background noise.
- ml_paired_event_correlation_1_2_rFLOAT
Pearson correlation coefficient for amplitudes of 1st:2nd pulses in 50Hz trains.
- ml_paired_event_correlation_1_2_pFLOAT
Pearson correlation p-value related to paired_event_correlation_1_2_r.
- ml_paired_event_correlation_2_4_rFLOAT
Pearson correlation coefficient for amplitudes of 1st:2nd pulses in 50Hz trains.
- ml_paired_event_correlation_2_4_pFLOAT
Pearson correlation p-value related to paired_event_correlation_1_2_r.
- ml_paired_event_correlation_4_8_rFLOAT
Pearson correlation coefficient for amplitudes of 1st:2nd pulses in 50Hz trains.
- ml_paired_event_correlation_4_8_pFLOAT
Pearson correlation p-value related to paired_event_correlation_1_2_r.
- metaVARCHAR
Pipeline
- class aisynphys.database.schema.Pipeline(**kwargs)
Sqlalchemy model for “Pipeline” database table.
Stores information about which pipeline analysis jobs were run, when, and whether there was an error.
- Attributes
- idINTEGER
- module_nameVARCHAR
The name of the pipeline module that generated this result
- job_idVARCHAR
Unique value identifying the job that was processed
- finish_timeDATETIME
The date/time when this job completed processing
- successBOOLEAN
Whether the job completed successfully
- errorVARCHAR
Error or warning messages generated during job processing
- metaVARCHAR