A circuit mechanism for decision-making biases and NMDA receptor hypofunction
- Department of Clinical and Movement Neurosciences, University College London, United Kingdom
- Department of Physics, Yale University, United States
- Department of Psychiatry, Yale University School of Medicine, United States
- Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom
- Max Planck-UCL Centre for Computational Psychiatry and Aging, University College London, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, United Kingdom
Figures
Figure 1
An evidence-varying decision-making task for macaque monkeys.
(A) Task design. Two streams of stimuli were presented to a monkey, both of which consisted of a sequence of eight samples of bars of varying heights. Depending on the contextual cue shown at the …
Figure 2 with 1 supplement
Subjects use evidence presented throughout the trial to guide their choices.
(A-B) Choice accuracy plotted as a function of the amount of evidence in favour of the best option. Lines are a psychometric fit to the data. (C-D) Logistic regression coefficients reveal the …
Figure 2—figure supplement 1
Subjects use evidence presented throughout the trial to guide their choices – data separated by ‘ChooseTall’ and ‘ChooseShort’ trials.
The psychometric functions and evidence weightings are very similar on ‘ChooseTall’ (red) and ‘ChooseShort’ (blue) trials. (A–B) Choice accuracy plotted as a function of the amount of evidence in …
Figure 3 with 2 supplements
Subjects show a pro-variance bias in their choices on Narrow-Broad Trials, mirroring previous findings in human subjects.
(A) The narrow-broad trials include three types of conditions, where either the narrow stream is correct (brown), the broad stream is correct (blue), or the difference in mean evidence is small …
Figure 3—figure supplement 1
Extra Information on Narrow-Broad Trials, separated by subjects.
(A) The generating process of the narrow-correct trials, for each narrow (brown) and broad (blue) stimuli sample. A full stream sequentially presents 8 such stimuli, each for 200ms with a 50ms …
Figure 3—figure supplement 2
Extra Information on Narrow-Broad Trials, separated by ‘ChooseTall’ and ‘ChooseShort’ trials.
The findings are very similar on ‘ChooseTall’ (red) and ‘ChooseShort’ (blue) trials. (A) The accuracy of Monkey A in the narrow-correct and broad-correct trials. Monkey A was significantly more …
Figure 4 with 3 supplements
Subjects show a pro-variance bias in their choices on regular trials.
For these analyses, stimulus streams were divided into ‘Lower SD’ or ‘Higher SD’ options post-hoc, on a trial-wise basis. (A) On regular trials, the mean evidence of each stream was independent. (B) …
Figure 4—figure supplement 1
Extra information on Regular Trials, separated by subjects.
In the regular-trials, each of the two streams is randomly chosen to be either narrow (), or broad (), then divided into ‘Lower SD’ or ‘Higher SD’ options post-hoc, depending on the sampled …
Figure 4—figure supplement 2
Extra information on Regular Trials, separated by ‘ChooseTall’ and ‘ChooseShort’ trials.
The findings are very similar on both trial types. (A) The psychometric function of Monkey A when either the ‘Lower SD’ (brown) or ‘Higher SD’ (blue) stream is correct, on ‘ChooseTall’ trials. (B) A …
Figure 4—figure supplement 3
Extra information on Regular Trials – the subjects do not show a frequent winner bias.
(A) A regression model using evidence mean and the number of local winners to predict Monkey A’s choices. This shows that after controlling for mean evidence, Monkey A did not have a frequent winner …
Figure 5 with 2 supplements
Spiking cortical circuit model reproduces pro-variance bias.
(A) Circuit model schematic. The model consists of two excitatory neural populations which receive separate inputs (IA and IB), each reflecting the momentary evidence for one of the two stimuli …
Figure 5—figure supplement 1
Extended regression results on the circuit model performance.
(A) Circuit model schematic. The model consists of two excitatory populations which receive separate inputs, reflecting evidence for the two stimuli streams. Each population integrates evidence due …
Figure 5—figure supplement 2
Pro-variance bias and temporal weightings in trials separated with more or less total evidence, for circuit model and monkey data.
(A–C) Regression analysis of the circuit model choices, using evidence mean and variability as predictors, on all regular trials (grey), half of the regular trials with more total evidence (pink), …
Figure 6 with 1 supplement
Mean-Field model explanation for pro-variance bias.
(A) The mean-field model of the circuit, with two variables representing evidence for the two options. For simplicity, we assume one stream is narrow and one is broad, and label the populations …
Figure 6—figure supplement 1
Extended regression results on the mean-field model performance.
(A) The mean-field model consists of two variables which represent the accumulated evidence for the two choice options. The two variables demonstrate self-excitation and mutual inhibition. (B) …
Figure 7 with 4 supplements
Predictions for E/I perturbations of the Spiking Circuit Model.
(A) Model perturbation schematic. Three potential perturbations are considered: lowered E/I (via NMDA-R hypofunction on excitatory pyramidal neurons), elevated E/I (via NMDA-R hypofunction on …
Figure 7—figure supplement 1
Model perturbations do not influence decision-making strategy.
(A) Model perturbation schematic. Three potential perturbations are considered: lowered E/I (via NMDA-R hypofunction on excitatory pyramidal neurons), elevated E/I (via NMDA-R hypofunction on …
Figure 7—figure supplement 2
Regression analysis using evidence mean and evidence variability to predict choice, under simultaneous NMDA-R hypofunctions on excitatory and inhibitory neurons.
(A) The mean evidence regression coefficient for various models of NMDA-R hypofunctions on excitatory () and inhibitory () neurons. (B) The evidence standard deviation regression coefficient for …
Figure 7—figure supplement 3
Regression analysis using mean, maximum, minimum, first, and last evidence values of each of the left and right streams as regressors, under simultaneous NMDA-R hypofunctions on excitatory and inhibitory neurons.
Each subplot shows the average of the left and right regressors of the corresponding variable. (A) Mean evidence regression coefficient for various models of NMDA-R hypofunctions on excitatory () …
Figure 7—figure supplement 4
Regression coefficients and PVB index as a function of sensory deficit.
(A–C) Regression model with mean evidence and evidence standard deviation, and the resulting PVB index. The PVB index increases at very large sensory deficits, in a regime with minimal decision …
Figure 8 with 9 supplements
Experimental effects of ketamine on evidence accumulation behaviour produce an increased pro-variance bias, consistent with lowered excitation-inhibition balance.
(A) Mean percentage of correct choices across sessions made by monkeys relative to the injection of ketamine (red) or saline (blue). Shaded region denotes ‘on-drug’ trials (trials 5–30 min after …
Figure 8—figure supplement 1
Extra information on ketamine experiments, separated by subjects.
(A) Mean percentage of correct choices across sessions made by Monkey A relative to the injection of ketamine (red) or saline (blue). (B) The psychometric function of Monkey A when either the ‘Lower …
Figure 8—figure supplement 2
Behavioural effects of ketamine on the pro-variance bias and temporal weightings are not explained by lapsing.
Results from Figure 8—figure supplement 1 are replicated with an extended model which included a lapse term. (A) Ketamine injection impairs the behaviour of Monkey A, in a manner consistent with the …
Figure 8—figure supplement 3
Time course of ketamine’s influence on pro-variance bias.
(A) The time course of the pro-variance bias index (PVB) is shown for Monkey A. The PVB index is significantly raised for around 20 min following ketamine administration (red). The black horizontal …
Figure 8—figure supplement 4
Cosine similarity of various perturbation effects in the circuit model, to the effect of ketamine injections on monkey behaviour.
(A) Schematic of the similarity measure. The effect of ketamine perturbation to monkey choice behaviour (with lapse rate accounted for) is represented as the relative change in regression …
Figure 8—figure supplement 5
Euclidean distance of various perturbation effects in the circuit model, to the effect of ketamine injections on monkey behaviour.
(A) Schematic of the dissimilarity measure. The effect of ketamine perturbation to monkey choice behaviour (with lapse rate accounted for) is represented as the relative change in regression …
Figure 8—figure supplement 6
Kullback–Leibler (KL) divergence from monkey behavior with saline or ketamine to circuit models with various perturbations.
(A) KL divergence between Monkey A saline data and circuit models with various degrees of NMDA-R hypofunction on excitatory () and inhibitory () neurons. Lower KL divergence between data and …
Figure 8—figure supplement 7
Psychometric function of monkeys under ketamine injection, and circuit model with large sensory deficit.
(A) Psychometric function of Monkey A under ketamine injection, replotted from Figure 8—figure supplement 1. (B) Psychometric function of Monkey H under ketamine injection, replotted from Figure …
Figure 8—figure supplement 8
Predictions for E/I perturbations of the Spiking Circuit Model, with built-in Monkey A lapse rate, compared with Monkey A behaviour.
For each circuit model (control, lowered E/I, elevated E/I, sensory deficit), a proportion of trials are selected and the corresponding choices are randomly shuffled to one of the two choices, with …
Figure 8—figure supplement 9
Predictions for E/I perturbations of the Spiking Circuit Model, with built-in Monkey H lapse rate, compared with Monkey H behaviour.
For each circuit model (control, lowered E/I, elevated E/I, sensory deficit), a proportion of trials are selected and the corresponding choices are randomly shuffled to one of the two choices, with …
Author response image 1
Animals rarely fail to complete trials when administered with ketamine.
The proportion of incomplete trials that occurred between 5 minutes and 30 minutes relative to drug administration. Errorbars indicate the standard error, each dot represents an individual session. …
Author response image 2
Incorporating a lapsing parameter does not greatly influence coefficients from the original logistic model for the PVB analysis.
(A) The mean evidence regression coefficient under saline (blue) and ketamine (red) under logistic regression with (no hatches) or without (hatched) a lapse term, using Monkey A data. (B) Same as …
Tables
Author response table 1
| Condition | Variable | Description |
|---|---|---|
| “Select Higher” | mean(L) | Average height of the 8 bars on the left side of the screen |
| “Select Higher” | mean(R) | Average height of the 8 bars on the right side of the screen |
| “Select Higher” | std(L) | Standard deviation of the heights of the 8 bars on the left side of the screen |
| “Select Higher” | std(R) | Standard deviation of the heights of the 8 bars on the right side of the screen |
| “Select Lower” | mean(L) | Average of (100 – Bar Height) for the 8 stimuli on the left side of the screen |
| “Select Lower” | mean(R) | Average of (100 – Bar Height) for the 8 stimuli on the right side of the screen |
| “Select Lower” | std(L) | Standard deviation of (100 – Bar Height) for the 8 stimuli on the left side of the screen |
| “Select Lower” | std(R) | Standard deviation of (100 – Bar Height) for the 8 stimuli on the right side of the screen |
Author response table 2
| Authors | Journal | Intramuscular Ketamine Doses Used |
|---|---|---|
| (M. Wang, Yang et al., 2013) | Neuron | 0.5-1.5 mg/kg |
| (Blackman, Macdonald et al., 2013) | Neuropsychopharmacology | 0.32–0.57 mg/kg |
| (Ma, Skoblenick et al., 2015) | Journal of Neuroscience | 0.4 mg/kg |
| (Ma, Skoblenick et al., 2018) | Journal of Neuroscience | 0.4 – 0.7 mg/kg |
| (Shen, Kalwarowsky et al., 2010) | Journal of Neuroscience | 0.25 – 1 mg/kg |
| (K. J. Skoblenick, Womelsdorf et al., 2016) | Cerebral Cortex | 0.4 mg/kg |
| (K. Skoblenick and Everling, 2014) | Journal of Cognitive Neuroscience | 0.4 mg/kg |
| (K. Skoblenick and Everling, 2012) | Journal of Neuroscience | 0.4 – 0.8 mg/kg |
| (Taffe, Davis et al., 2002) | Psychopharmacology | 0.3- 1.7 mg/kg |
| (Condy, Wattiez et al., 2005) | Biological Psychiatry | 0.2 – 1.2 mg/kg |
| (Stoet and Snyder, 2006) | Neuropsychopharmacology | 0.07 – 1 mg/kg |
Additional files
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Supplementary file 1
Difference in log-likelihood of Full regression model (mean, SD, max, min, first, last of evidence values; Equation 6 in Materials and methods) vs reduced model, for each monkey and the circuit model.
Log-likelihood values were calculated using a cross-validation procedure (see Materials and methods). Column label refers to the removed regressor. Positive values indicate the full regression model performs better. Values depend on the number of completed trials, which differed both between subjects and the circuit model. For both monkeys and the circuit model, mean evidence is clearly the most important driver of choice behaviour, followed by first and last evidence samples which reflects the primacy bias. Finally, evidence standard deviation (SD) has a stronger effect than maximum and minimum evidence samples (Max and Min).
- https://cdn.elifesciences.org/articles/53664/elife-53664-supp1-v3.docx
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Supplementary file 2
Difference in log-likelihood of regression models including either evidence standard deviation (SD) or both maximum and minimum evidence (Max and Min) as regressors, for each monkey and the circuit model.
Log-likelihood values were calculated using a cross-validation procedure (see Materials and methods). Column label refers to the regressors additional to either SD or Max and Min. Positive values indicate the regression model with SD performs better than that with Max and Min. Values depend on the number of completed trials, which differed both between subjects and the circuit model. Regardless of whether first and last evidence sample regressors are included, the models with standard deviation of evidence have higher log-likelihoods than the models with maximum and minimum evidence samples, indicating a better explanation of the data by standard deviation than by maximum and minimum evidence samples.
- https://cdn.elifesciences.org/articles/53664/elife-53664-supp2-v3.docx
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Supplementary file 3
Increase in log-likelihood of various regression models (regressors in column labels) due to inclusion of evidence standard deviation as a regressor, for each monkey and the circuit model.
Log-likelihood values were calculated using a cross-validation procedure (see Materials and methods). Values depend on the number of completed trials, which differed both between subjects and the circuit model. Positive values across the table indicates the evidence standard deviation regressor robustly improves model performance for all models examined.
- https://cdn.elifesciences.org/articles/53664/elife-53664-supp3-v3.docx
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Supplementary file 4
Difference in log-likelihood of regression models including either evidence standard deviation (SD) or both maximum and minimum evidence (Max and Min) as regressors, for each monkey with saline or ketamine injection.
Log-likelihood values were calculated using a cross-validation procedure (see Materials and methods). Column label refers to the regressors additional to either SD or Max and Min. Positive values indicate the regression model with SD performs better than that with Max and Min. Values depend on the number of completed trials, which differed across conditions. Regardless of whether first and last evidence sample regressors are included, the models with standard deviation of evidence have higher log-likelihoods than the models with maximum and minimum evidence samples, indicating a better explanation of the data by standard deviation than by maximum and minimum evidence samples. In particular, under ketamine injection, monkeys did not switch their strategy to primarily use maximum and minimum evidence samples (over standard deviation of evidence) to guide their choice.
- https://cdn.elifesciences.org/articles/53664/elife-53664-supp4-v3.docx
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Transparent reporting form
- https://cdn.elifesciences.org/articles/53664/elife-53664-transrepform-v3.docx
