Neuroscience Papers - Part 2

Meta

• Controversial questions https://sites.google.com/ccneuro.org/gac2020/home?authuser=0
• Prediction in science - How GR got accepted - https://www.jstor.org/stable/pdf/1704755.pdf?casa_token=SNoezC-1tacAAAAA:yoLc4OYCT5C_uTQGrAc8FxdYpux3cvYzmS0UGzKbszDjiEl3Z9eAWaGXFRZULA390HdyqnlI325nbLo6QRbw-EnaV8HLxikmsJPcuS6fpXnwX6ST9BY

Generalization in tasks

https://www.nature.com/articles/s41586-024-08145-x

Decision making

• Human RTnet model for object recognition - https://www.nature.com/articles/s41562-024-01914-8

• brain wide dynamics in decision making - https://www.nature.com/articles/s41586-024-07908-w

• Striatal pathways and decision making - https://www.cell.com/cell-reports/pdfExtended/S2211-1247(24)01077-5

• Decision making theory including non-task appropriate aspects(exploring, impulse) - https://www.biorxiv.org/content/10.1101/2022.06.24.497481v3.full.pdf

  Trials could be frequently occuring or rarely occuring. If they frequently, occur it is said “stakes are low” because one has many oppurtunity. If trials are rare, then stakes are high as u can’t afford to miss the rare trials.

  Quantitatively, stakes is sum of ITI + penalty time, divided by “time taken by uncertainity to reduce to 1/2”. Basically, telling how frequent the trials are compared to “uncertainity reducing time”

  As stakes increase, reaction time increase. Because it is important for animal to be accurate. So, it increases the bound(speed-accuracy tradeoff).

• https://elifesciences.org/articles/90859 - neural correlates of DV

Superior Colliculus in Decision making

• Genetically Defined Functional Modules for Spatial Orienting in the Mouse Superior Colliculus

• A neural mechanism for terminating decisions - https://www.sciencedirect.com/science/article/pii/S0896627323004002?via%3Dihub#fig5 Showing Sup. Colliculus is responsible for threshold, Intrapareterial region is for decision variable

• Cortico–basal ganglia circuit mechanism for a decision threshold in reaction time tasks : A comp model for calculating thresholds.

• CONCURRENT, DISTRIBUTED CONTROL OF SACCADE INITIATION IN THE FRONTAL EYE FIELD AND SUPERIOR COLLICULUS

Fractals in brain

https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=fractals+in+brain+networks&btnG=

Bayesian Inference:

Max Neural Likelihood(MNLE) - https://elifesciences.org/articles/77220#content

• Finding Likelihood function using Neural networks

Seq. Neural Posterior Estimation(SNPE) - https://elifesciences.org/articles/56261

• Finding Posterior directly from Neural Network

Drift Diffusion Models in 2 Alternate choice task:

Race between Proactive and reactive process- https://www.nature.com/articles/s41467-021-27302-8#Sec11

”Proactive responses are generated when the AI threshold is reached first; the choice is then defined as a direct read-out of the sign of the EA process 𝑥(𝑡) after the interrupted stimulus is integrated”

• Model parameters were estimated for each animal only based on RTs for all trials including FBs

• Slowing of responses due to fatigue or satisfied: account for the slowing of the responses within each session (Fig. 6a, b), AI drift scaled linearly with trial index k as V_A,k_ = _ν_A0 + _ν_trial·k, and we fitted the parameters _ν_A0 and _ν_trial

• Bias towards left or right: For biased trials, the value of the starting point was signed depending on the trial-dependent expectation of rewarded side b__k = ±1 , so that _Z_E = _z_E·b__k, where we fitted the parameter _z_E representing the magnitude of the animal’s expectation

• Not used choice data ??? “MLE values were obtained using RTs data only, and not choices”

• Extended DDM: evidence accumulations before the onset of stim, directly after fixation

• Wiener Process: https://galton.uchicago.edu/~lalley/Courses/313/BrownianMotionCurrent.pdf

Weber’s law and DDM - https://www.nature.com/articles/s41593-019-0439-7#Equ1

DDM review by Roger Ratcliff - https://www.cell.com/trends/cognitive-sciences/abstract/S1364-6613(16)00025-5?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS1364661316000255%3Fshowall%3Dtrue

Original DDM paper - Roger Ratcliff: A Theory of Memory Retrieval

DDM in value based tasks instead of sensory tasks - https://elifesciences.org/reviewed-preprints/96997

-Nested Sampling

Stats

• https://allendowney.blogspot.com/2011/05/there-is-only-one-test.html
• You are seeing how many times you get a difference like that and worse than that? If it happens several times, then fine. But if is happening only a few times, then getting a difference as bad as currently and worse than that is a low probable scenerio. So, the null hypothesis, which says that there is no much difference between model and reality are almost same is wrong.
• https://allendowney.blogspot.com/2016/06/there-is-still-only-one-test.html

Tools

• Spike Sorting with end to end neural network - https://arxiv.org/abs/2409.13067