Meeting Notes

  • Date: 2025-07-08
  • Time: 09:00 (PT)
  • Location: Teams Meeting
  • Presentations: @lrudelt @jeromelecoq

Agenda

  1. Lucas will introduce his analysis of response strength across time throughout a SLAP2 session
  2. Jerome will present the generic bonsai script that can cover all sessions context (motor, sequence, standard and jitter).

Meeting Recording

Meeting Notes

SLAP 2 Experiments: Jerome provided updates on SLAP 2 experiments, mentioning that they recorded pyramidal cells and VIP neurons, and deployed the stimulus discussed last week.

Experiment Details: Jerome updated on SLAP 2 experiments, noting recordings of pyramidal cells and VIP neurons, including two VIP neurons (one superficial and one deep layer) to compare their inputs.

Stimulus Deployment: The stimulus discussed last week was deployed with an extension requested by Lucas at the onset of the orientation block.

Data Packaging: Jerome mentioned efforts to package the data before mid-July, although he could not guarantee completion by that time.

Transient Dynamics Analysis: Lucas presented an analysis on transient dynamics of control and oddball responses, explaining the contextual modulation of responses depending on the predictive context.

Contextual Modulation: Lucas explained the concept of contextual modulation, where the same stimulus is shown under different conditions (redundant, deviant, and random control) to observe response differences.

Mismatch Negativity: Alexander raised a question about the importance of the control condition to avoid mistaking responses for oddball responses, which Lucas confirmed as crucial for accurate analysis.

Population Averages: Lucas presented population averages showing stronger responses to deviant stimuli compared to redundant contexts, emphasizing the importance of focusing on responsive ROIs.

Responsive ROIs: Lucas discussed the need to include only responsive ROIs in population averages to avoid dragging down the averages and missing effects.

Responsive ROIs: Lucas discussed the importance of focusing on responsive ROIs to get conclusive results, and explained how he defined responsiveness.

Defining Responsiveness: Lucas defined responsiveness as activity above one standard deviation of the baseline mean during any condition, explaining the need to include ROIs active during at least one condition.

Threshold Adjustment: Lucas adjusted the threshold to one standard deviation instead of 1.67 due to higher variability in synaptic data compared to soma data.

Statistical Measures: Alexander suggested using area under the curve instead of standard deviation for statistical measures, as it is independent of the assumption of normal distribution.

Statistical Measures: Alexander suggested using area under the curve instead of standard deviation for statistical measures, as it is independent of the assumption of normal distribution.

Temporal Evolution of Responses: Lucas analyzed the temporal evolution of average stimulus responses, showing how responses evolve over the experiment and the effect of synaptic depletion.

Response Evolution: Lucas presented the temporal evolution of average stimulus responses, showing initial strong responses followed by habituation and synaptic depletion.

Synaptic Depletion: Lucas explained synaptic depletion as a gradual decrease in responses due to repeated exposure to the same stimulus, leading to apparent long-term depression.

Control Conditions: Lucas compared responses during different control conditions, highlighting the release from synaptic depletion in the second control condition.

Transient Dynamics: Lucas emphasized the importance of considering transient dynamics in the analysis to avoid misinterpreting long-term depression effects.

Spatial Distribution Analysis: Jerome suggested following up with an analysis of the spatial distribution of the synaptic depletion effect to rule out intracellular mechanisms.

Comparison with Recent Study: Lucas compared their findings with a recent study, highlighting the importance of careful analysis and stimulus design to avoid misinterpretation of results.

Stimulus Design Discussion: Jerome presented the bonsai code for the stimulus design, explaining its components and functionality, and proposed discussing the design in more depth next week.

Bonsai Code: Jerome explained the bonsai code for stimulus design, detailing its components such as window setup, timing monitoring, manual experiment ending, data storage, color balance, and gamma calibration.

CSV Files: Jerome described the use of CSV files to store stimulus parameters for each block, allowing for random selection and reloading of previous behavior.

Phase Control: Jerome explained the conversion of the mouse wheel into temporal phase for controlling the gratings, with options to use predefined phases or read from the wheel.

Data Saving: Jerome highlighted the importance of saving stimulus tables and sending pulses to the NI card for time tracking.

Sensory Motor Mismatch Block: Karim suggested introducing Gray gaps in the sensory motor mismatch block to distinguish the visual flow from the running speed of the animal.

Control Blocks: Lucas questioned the rationale for having all control blocks in a single session, and Jerome explained that it allows for normalization and comparison across different contexts.