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Distinct relationships of parietal and prefrontal cortices to evidence accumulation.

Hanks TD, Kopec CD, Brunton BW, Duan CA, Erlich JC, Brody CD - Nature (2015)

Bottom Line: Gradual accumulation of evidence is thought to be fundamental for decision-making, and its neural correlates have been found in several brain regions.Classical analyses uncovered correlates of accumulating evidence, similar to previous observations in primates and also similar across the two regions.Our results place important constraints on the circuit logic of brain regions involved in decision-making.

View Article: PubMed Central - PubMed

Affiliation: 1] Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey 08544, USA [2] Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA.

ABSTRACT
Gradual accumulation of evidence is thought to be fundamental for decision-making, and its neural correlates have been found in several brain regions. Here we develop a generalizable method to measure tuning curves that specify the relationship between neural responses and mentally accumulated evidence, and apply it to distinguish the encoding of decision variables in posterior parietal cortex and prefrontal cortex (frontal orienting fields, FOF). We recorded the firing rates of neurons in posterior parietal cortex and FOF from rats performing a perceptual decision-making task. Classical analyses uncovered correlates of accumulating evidence, similar to previous observations in primates and also similar across the two regions. However, tuning curve assays revealed that while the posterior parietal cortex encodes a graded value of the accumulating evidence, the FOF has a more categorical encoding that indicates, throughout the trial, the decision provisionally favoured by the evidence accumulated so far. Contrary to current views, this suggests that premotor activity in the frontal cortex does not have a role in the accumulation process, but instead has a more categorical function, such as transforming accumulated evidence into a discrete choice. To probe causally the role of FOF activity, we optogenetically silenced it during different time points of the trial. Consistent with a role in committing to a categorical choice at the end of the evidence accumulation process, but not consistent with a role during the accumulation itself, a behavioural effect was observed only when FOF silencing occurred at the end of the perceptual stimulus. Our results place important constraints on the circuit logic of brain regions involved in decision-making.

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Rat behavior and example neuronsa, Mean psychometric function across all rats. Accuracy was highest for the largest click differences (the left and right endpoints of the curve) and lower for smaller click differences (the middle of the curve). b, Mean chronometric function across all rats. Trials were sorted by binned stimulus strength (difficulty), with mean click ratios ranging from 39:1 clicks/s for the easiest trials to 25:15 clicks/s for the hardest trials. In general, accuracy improved with longer stimulus durations. c, Mean psychophysical reverse correlation across all rats. This was calculated based on trials with minimum duration of at least 0.6 s. For each timepoint in each trial, we first computed the excess click rate difference (right - left clicks/s) relative to the value expected given the random processes used to generate the trial. These excess click rates were averaged separately for trials ending with a right choice (red) and for trials ending with a left choice (green). The separation between the two traces indicates how strongly clicks from the corresponding timepoint influence the final decision. d, Peri-event time histograms (PETHs) aligned to stimulus onset were calculated for 3 example PPC neurons. Trials were sorted into 4 stimulus strength bins for each neuron. Green traces correspond to the preferred-direction stimuli and red traces correspond to anti-preferred-direction stimuli. Darker colors correspond to stronger stimuli (less difficult) and brighter colors correspond to weaker stimuli (more difficult). e, PETHs for 3 example FOF neurons using the same conventions. In both regions, individual neurons exhibit ramping activity that depends on stimulus strength.
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Figure 5: Rat behavior and example neuronsa, Mean psychometric function across all rats. Accuracy was highest for the largest click differences (the left and right endpoints of the curve) and lower for smaller click differences (the middle of the curve). b, Mean chronometric function across all rats. Trials were sorted by binned stimulus strength (difficulty), with mean click ratios ranging from 39:1 clicks/s for the easiest trials to 25:15 clicks/s for the hardest trials. In general, accuracy improved with longer stimulus durations. c, Mean psychophysical reverse correlation across all rats. This was calculated based on trials with minimum duration of at least 0.6 s. For each timepoint in each trial, we first computed the excess click rate difference (right - left clicks/s) relative to the value expected given the random processes used to generate the trial. These excess click rates were averaged separately for trials ending with a right choice (red) and for trials ending with a left choice (green). The separation between the two traces indicates how strongly clicks from the corresponding timepoint influence the final decision. d, Peri-event time histograms (PETHs) aligned to stimulus onset were calculated for 3 example PPC neurons. Trials were sorted into 4 stimulus strength bins for each neuron. Green traces correspond to the preferred-direction stimuli and red traces correspond to anti-preferred-direction stimuli. Darker colors correspond to stronger stimuli (less difficult) and brighter colors correspond to weaker stimuli (more difficult). e, PETHs for 3 example FOF neurons using the same conventions. In both regions, individual neurons exhibit ramping activity that depends on stimulus strength.

Mentions: We trained rats on a previously developed decision task in which subjects accumulate sensory evidence over many hundreds of milliseconds to inform a binary left-right choice (“Poisson Clicks” task, Fig. 1a, Extended Data Fig. 1a–c)10. On each trial, rats kept their nose in a central port during the presentation of two simultaneous trains of randomly-timed auditory clicks, one played from a speaker to their left and the other from a speaker to their right. At the end of the variable-duration stimulus, the rat’s task was to decide which side had played the greater total number of clicks (Fig. 1a). Easy trials had a large mean rate difference between the two click trains (e.g., 39:1 clicks/sec), while difficult trials had a small mean rate difference (e.g., 21:19 clicks/sec). Accumulation of evidence models predict that averaging within a given difficulty class will produce a mean trajectory for the accumulated evidence that gradually ramps over time with a slope proportional to the mean strength of the sensory evidence (Fig. 1b). This type of correlate of evidence accumulation has been reported in several interconnected primate brain regions, including the PPC and frontal eye fields3–5,7,8,11. To examine whether signatures of evidence accumulation are present in the rodent brain, we recorded from 394 neurons in PPC of 4 rats and 397 neurons in FOF of 6 rats while they performed the Poisson Clicks task. These two areas that have been suggested as potential rat homologues of primate PPC and FEF12,13. We recorded all isolatable neurons encountered regardless of response properties. Ninety-three neurons in PPC (23%) and 128 neurons in FOF (32%) exhibited firing rates during the pre-movement period (from stimulus onset to center port withdrawal) that were significantly different (p<0.05) for trials that subsequently ended with a right versus a left choice. This pre-movement side selectivity is consistent with previous findings in both rat PPC14,15 and FOF13. We focus on these pre-movement side-selective neurons because they are most likely to play a role in decision formation.


Distinct relationships of parietal and prefrontal cortices to evidence accumulation.

Hanks TD, Kopec CD, Brunton BW, Duan CA, Erlich JC, Brody CD - Nature (2015)

Rat behavior and example neuronsa, Mean psychometric function across all rats. Accuracy was highest for the largest click differences (the left and right endpoints of the curve) and lower for smaller click differences (the middle of the curve). b, Mean chronometric function across all rats. Trials were sorted by binned stimulus strength (difficulty), with mean click ratios ranging from 39:1 clicks/s for the easiest trials to 25:15 clicks/s for the hardest trials. In general, accuracy improved with longer stimulus durations. c, Mean psychophysical reverse correlation across all rats. This was calculated based on trials with minimum duration of at least 0.6 s. For each timepoint in each trial, we first computed the excess click rate difference (right - left clicks/s) relative to the value expected given the random processes used to generate the trial. These excess click rates were averaged separately for trials ending with a right choice (red) and for trials ending with a left choice (green). The separation between the two traces indicates how strongly clicks from the corresponding timepoint influence the final decision. d, Peri-event time histograms (PETHs) aligned to stimulus onset were calculated for 3 example PPC neurons. Trials were sorted into 4 stimulus strength bins for each neuron. Green traces correspond to the preferred-direction stimuli and red traces correspond to anti-preferred-direction stimuli. Darker colors correspond to stronger stimuli (less difficult) and brighter colors correspond to weaker stimuli (more difficult). e, PETHs for 3 example FOF neurons using the same conventions. In both regions, individual neurons exhibit ramping activity that depends on stimulus strength.
© Copyright Policy - permissions-link
Related In: Results  -  Collection

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Figure 5: Rat behavior and example neuronsa, Mean psychometric function across all rats. Accuracy was highest for the largest click differences (the left and right endpoints of the curve) and lower for smaller click differences (the middle of the curve). b, Mean chronometric function across all rats. Trials were sorted by binned stimulus strength (difficulty), with mean click ratios ranging from 39:1 clicks/s for the easiest trials to 25:15 clicks/s for the hardest trials. In general, accuracy improved with longer stimulus durations. c, Mean psychophysical reverse correlation across all rats. This was calculated based on trials with minimum duration of at least 0.6 s. For each timepoint in each trial, we first computed the excess click rate difference (right - left clicks/s) relative to the value expected given the random processes used to generate the trial. These excess click rates were averaged separately for trials ending with a right choice (red) and for trials ending with a left choice (green). The separation between the two traces indicates how strongly clicks from the corresponding timepoint influence the final decision. d, Peri-event time histograms (PETHs) aligned to stimulus onset were calculated for 3 example PPC neurons. Trials were sorted into 4 stimulus strength bins for each neuron. Green traces correspond to the preferred-direction stimuli and red traces correspond to anti-preferred-direction stimuli. Darker colors correspond to stronger stimuli (less difficult) and brighter colors correspond to weaker stimuli (more difficult). e, PETHs for 3 example FOF neurons using the same conventions. In both regions, individual neurons exhibit ramping activity that depends on stimulus strength.
Mentions: We trained rats on a previously developed decision task in which subjects accumulate sensory evidence over many hundreds of milliseconds to inform a binary left-right choice (“Poisson Clicks” task, Fig. 1a, Extended Data Fig. 1a–c)10. On each trial, rats kept their nose in a central port during the presentation of two simultaneous trains of randomly-timed auditory clicks, one played from a speaker to their left and the other from a speaker to their right. At the end of the variable-duration stimulus, the rat’s task was to decide which side had played the greater total number of clicks (Fig. 1a). Easy trials had a large mean rate difference between the two click trains (e.g., 39:1 clicks/sec), while difficult trials had a small mean rate difference (e.g., 21:19 clicks/sec). Accumulation of evidence models predict that averaging within a given difficulty class will produce a mean trajectory for the accumulated evidence that gradually ramps over time with a slope proportional to the mean strength of the sensory evidence (Fig. 1b). This type of correlate of evidence accumulation has been reported in several interconnected primate brain regions, including the PPC and frontal eye fields3–5,7,8,11. To examine whether signatures of evidence accumulation are present in the rodent brain, we recorded from 394 neurons in PPC of 4 rats and 397 neurons in FOF of 6 rats while they performed the Poisson Clicks task. These two areas that have been suggested as potential rat homologues of primate PPC and FEF12,13. We recorded all isolatable neurons encountered regardless of response properties. Ninety-three neurons in PPC (23%) and 128 neurons in FOF (32%) exhibited firing rates during the pre-movement period (from stimulus onset to center port withdrawal) that were significantly different (p<0.05) for trials that subsequently ended with a right versus a left choice. This pre-movement side selectivity is consistent with previous findings in both rat PPC14,15 and FOF13. We focus on these pre-movement side-selective neurons because they are most likely to play a role in decision formation.

Bottom Line: Gradual accumulation of evidence is thought to be fundamental for decision-making, and its neural correlates have been found in several brain regions.Classical analyses uncovered correlates of accumulating evidence, similar to previous observations in primates and also similar across the two regions.Our results place important constraints on the circuit logic of brain regions involved in decision-making.

View Article: PubMed Central - PubMed

Affiliation: 1] Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey 08544, USA [2] Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA.

ABSTRACT
Gradual accumulation of evidence is thought to be fundamental for decision-making, and its neural correlates have been found in several brain regions. Here we develop a generalizable method to measure tuning curves that specify the relationship between neural responses and mentally accumulated evidence, and apply it to distinguish the encoding of decision variables in posterior parietal cortex and prefrontal cortex (frontal orienting fields, FOF). We recorded the firing rates of neurons in posterior parietal cortex and FOF from rats performing a perceptual decision-making task. Classical analyses uncovered correlates of accumulating evidence, similar to previous observations in primates and also similar across the two regions. However, tuning curve assays revealed that while the posterior parietal cortex encodes a graded value of the accumulating evidence, the FOF has a more categorical encoding that indicates, throughout the trial, the decision provisionally favoured by the evidence accumulated so far. Contrary to current views, this suggests that premotor activity in the frontal cortex does not have a role in the accumulation process, but instead has a more categorical function, such as transforming accumulated evidence into a discrete choice. To probe causally the role of FOF activity, we optogenetically silenced it during different time points of the trial. Consistent with a role in committing to a categorical choice at the end of the evidence accumulation process, but not consistent with a role during the accumulation itself, a behavioural effect was observed only when FOF silencing occurred at the end of the perceptual stimulus. Our results place important constraints on the circuit logic of brain regions involved in decision-making.

Show MeSH
Related in: MedlinePlus