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Maryam Tohidi-Moghaddam

Publications and source records attributed to Maryam Tohidi-Moghaddam.

2 recordsLinked to original sources

Sequence-dependent sensitivity explains the accuracy of decisions when cues are separated with a gap

Most decisions require information gathering from a stimulus presented with different gaps. Indeed, the brain process of this integration is rarely ambiguous. Recently, it has been claimed that humans can optimally integrate the information of two discrete pulses independent of the temporal gap between them. Interestingly, subjects' performance on such a task, with two discrete pulses, is superior to what a perfect accumulator can predict. Although numerous neuronal and descriptive models have been proposed to explain the mechanism of perceptual decision-making, none can explain human behavior in this two-pulse task. In order to investigate the mechanism of decision-making on the noted tasks, a set of modified drift-diffusion models based on different hypotheses were used. Model comparisons clarified that, in a sequence of information arriving at different times, the accumulated information of earlier evidence affects the process of information accumulation of later evidence. It was shown that the rate of information extraction depends on whether the pulse is the first or the second one. The proposed model can also explain the stronger effect of the second pulse as shown by Kiani et al. 2013.

q-bio.NC↗

Residual Information of Previous Decision Affects Evidence Accumulation in Current Decision

Bias in perceptual decisions comes to pass when the advance knowledge colludes with the current sensory evidence in support of the final choice. The literature on decision making suggests two main hypotheses to account for this kind of bias: internal bias signals are derived from (a) the residual of motor response-related signals, and (b) the sensory information residues of the decisions that we made in the past. Beside these hypotheses, a credible hypothesis proposed by this study to explain the cause of decision biasing, suggests that the decision-related neuron can make use of the residual information of the previous decision for the current decision. We demonstrate the validity of this assumption, first by performing behavioral experiments based on the two-alternative forced-choice (TAFC) discrimination of motion direction paradigms and then, we modified the pure drift-diffusion model (DDM) based on accumulation to the bound mechanism to account for the sequential effect. In both cases, the trace of the previous trial influences the current decision. Results indicate that the probability of being correct in a current decision increases if it is in line with the previously made decision. Also, the model that keeps the previous decision information provides a better fit to the behavioral data. Our findings suggest that the state of a decision variable which is represented in the activity of decision-related neurons after crossing the bound (in the previous decision) can accumulate with the decision variable for the current decision in consecutive trials.

q-bio.NC↗