Bharathi Jagadeesh

Neural responses throughout the sensory system are affected by stimulus history. In the inferotemporal cortex (IT)—an area important for processing information about object shape—there is a substantially reduced response to the second presentation of an image. Understanding the mechanisms underlying repetition suppression may provide important insights into the circuitry that generates responses in IT. In addition, repetition suppression may have important perceptual consequences. The characteristics of repetition suppression in IT are poorly understood, and the details, including the interaction between the content of the first and second stimulus and the time course of suppression, are not clear. Here, we examined the time course of suppression in IT by varying both the duration and stimulus content of two stimuli presented in sequence. The data show that the degree of suppression does not depend directly on the response evoked by the first stimulus in the recorded neuron. Repetition suppression was also limited in duration, peaking at ≈ 200 ms after the onset of the second (test) image and disappearing before the end of the response. Neural selectivity to a continuum of related images was enhanced if the first stimulus produced a weak response in the cell. The dynamics of the response suggests that different parts of the input and recurrent circuitry that gives rise to neural responses in IT are differentially modulated by repetition suppression. The selectivity of the sustained response was preserved in spite of substantial suppression of the early part of the response. The data suggest that suppression in IT is a property of the input and recurrent circuitry in IT and is not directly related to the degree of response in the recorded neuron itself.

How does the brain dynamically convert incoming sensory data into a representation useful for classification? Neurons in inferior temporal (IT) cortex are selective for complex visual stimuli, but their response dynamics during perceptual classification is not well understood. We studied IT dynamics in monkeys performing a classification task. The monkeys were shown visual stimuli that were morphed (interpolated) between pairs of familiar images. Their ability to classify the morphed images depended systematically on the degree of morph. IT neurons were selected that responded more strongly to one of the 2 familiar images (the effective image). The responses tended to peak ∼120 ms following stimulus onset with an amplitude that depended almost linearly on the degree of morph. The responses then declined, but remained above baseline for several hundred ms. This sustained component remained linearly dependent on morph level for stimuli more similar to the ineffective image but progressively converged to a single response profile, independent of morph level, for stimuli more similar to the effective image. Thus, these neurons represented the dynamic conversion of graded sensory information into a task-relevant classification. Computational models suggest that these dynamics could be produced by attractor states and firing rate adaptation within the population of IT neurons.

With experience, an object can become behaviorally relevant and thereby quickly attract our interest when presented in a visual scene. A likely site of these learning effects is anterior inferior temporal (aIT) cortex, where neurons are thought to participate in the filtering of irrelevant information out of complex visual displays. We trained monkeys to saccade consistently to one of two pictures in an array, in return for a reward. The array was constructed by pairing two stimuli, one of which elicited a good response from the cell when presented alone (“good” stimulus) and the other of which elicited a poor response (“poor” stimulus). The activity of aIT cells was recorded while monkeys learned to saccade to either the good or poor stimulus in the array. We found that neuronal responses to the array were greater (before the saccade occurred) when training reinforced a saccade to the good stimulus than when training reinforced a saccade to the poor stimulus. This difference was not present on incorrect trials, i.e., when saccades to the incorrect stimulus were made. Thus the difference in activity was correlated with performance. The response difference grew over the course of the recording session, in parallel with the improvement in performance. The response difference was not preceded by a difference in the baseline activity of the cells, unlike what was found in studies of cued visual search and working memory in aIT cortex. Furthermore, we found similar effects in a version of the task in which any of 10 possible pairs of stimuli, prelearned before the recording session, could appear on a given trial, thereby precluding a working memory strategy. The results suggest that increasing the behavioral significance of a stimulus through training alters the neural representation of that stimulus in aIT cortex. As a result, neurons responding to features of the relevant stimulus may suppress neurons responding to features of irrelevant stimuli.