Thursday, August 04, 2016

Distinguishing brain correlations from causes.

Many researchers, even though they know better, fall into the trap of assuming that correlations are causes (i.e., if brain activity X occurs just before or at the same time as action Y, it must be causing Y.) Katz et al. offer a nice example of this in looking at a brain region (the lateral intraparietal (LIP) cortex) whose activity reflects deciding on the direction of a moving set of dots. When this region was inactivated in rhesus macague monkeys performing a motion direction discrimination, it had no effect on decision making performance. But, when area MT (a motion detection area that shows only weak correlations with choices) was inhibited, performance was profoundly impaired. This suggests that larger networks should always be considered even in what seem to be simple decisions. The abstract:
During decision making, neurons in multiple brain regions exhibit responses that are correlated with decisions1. However, it remains uncertain whether or not various forms of decision-related activity are causally related to decision making. Here we address this question by recording and reversibly inactivating the lateral intraparietal (LIP) and middle temporal (MT) areas of rhesus macaques performing a motion direction discrimination task. Neurons in area LIP exhibited firing rate patterns that directly resembled the evidence accumulation process posited to govern decision making, with strong correlations between their response fluctuations and the animal’s choices. Neurons in area MT, in contrast, exhibited weak correlations between their response fluctuations and choices, and had firing rate patterns consistent with their sensory role in motion encoding. The behavioural impact of pharmacological inactivation of each area was inversely related to their degree of decision-related activity: while inactivation of neurons in MT profoundly impaired psychophysical performance, inactivation in LIP had no measurable impact on decision-making performance, despite having silenced the very clusters that exhibited strong decision-related activity. Although LIP inactivation did not impair psychophysical behaviour, it did influence spatial selection and oculomotor metrics in a free-choice control task. The absence of an effect on perceptual decision making was stable over trials and sessions and was robust to changes in stimulus type and task geometry, arguing against several forms of compensation. Thus, decision-related signals in LIP do not appear to be critical for computing perceptual decisions, and may instead reflect secondary processes. Our findings highlight a dissociation between decision correlation and causation, showing that strong neuron-decision correlations do not necessarily offer direct access to the neural computations underlying decisions.

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