Bidirectional signaling between neocortex and limbic cortex has been hypothesized to contribute to the retrieval of long-term memory. We tested this hypothesis by comparing the time courses of perceptual and memory-retrieval signals in two neighboring areas in temporal cortex, area TE (TE) and perirhinal cortex (PRh), while monkeys were performing a visual pair-association task. Perceptual signal reached TE before PRh, confirming its forward propagation. In contrast, memory-retrieval signal appeared earlier in PRh, and TE neurons were then gradually recruited to represent the sought target. A reasonable interpretation of this finding is that the rich backward fiber projections from PRh to TE may underlie the activation of TE neurons that represent a visual object retrieved from long-term memory.

Microsaccades exhibit systematic oscillations in direction after spatial cueing, and these oscillations correlate with facilitatory and inhibitory changes in behavioral performance in the same tasks. However, independent of cueing, facilitatory and inhibitory changes in visual sensitivity also arise pre-microsaccadically. Given such pre-microsaccadic modulation, an imperative question to ask becomes: how much of task performance in spatial cueing may be attributable to these peri-movement changes in visual sensitivity? To investigate this question, we adopted a theoretical approach. We developed a minimalist model in which: (1) microsaccades are repetitively generated using a rise-to-threshold mechanism, and (2) pre-microsaccadic target onset is associated with direction-dependent modulation of visual sensitivity, as found experimentally. We asked whether such a model alone is sufficient to account for performance dynamics in spatial cueing. Our model not only explained fine-scale microsaccade frequency and direction modulations after spatial cueing, but it also generated classic facilitatory (i.e., attentional capture) and inhibitory [i.e., inhibition of return (IOR)] effects of the cue on behavioral performance. According to the model, cues reflexively reset the oculomotor system, which unmasks oscillatory processes underlying microsaccade generation; once these oscillatory processes are unmasked, “attentional capture” and “IOR” become direct outcomes of pre-microsaccadic enhancement or suppression, respectively. Interestingly, our model predicted that facilitatory and inhibitory effects on behavior should appear as a function of target onset relative to microsaccades even without prior cues. We experimentally validated this prediction for both saccadic and manual responses. We also established a potential causal mechanism for the microsaccadic oscillatory processes hypothesized by our model. We used retinal-image stabilization to experimentally control instantaneous foveal motor error during the presentation of peripheral cues, and we found that post-cue microsaccadic oscillations were severely disrupted. This suggests that microsaccades in spatial cueing tasks reflect active oculomotor correction of foveal motor error, rather than presumed oscillatory covert attentional processes. Taken together, our results demonstrate that peri-microsaccadic changes in vision can go a long way in accounting for some classic behavioral phenomena.

The macaque inferotemporal (IT) cortex, which serves as the storehouse of visual long-term memory, consists of two distinct but mutually interconnected areas: area TE (TE) and area 36 (A36). In the present study, we tested whether memory encoding is put forward at this stage, i.e., whether association between the representations of different but semantically linked objects proceeds forward from TE to A36. To address this question, we trained monkeys in a pair-association (PA) memory task, after which single-unit activities were recorded from TE and A36 during PA trials. Neurons in both areas showed stimulus-selective cue responses (347 in TE, 76 in A36; "cue-selective neurons") that provided, at the population level, mnemonic linkage between the paired associates. The percentage of neurons in which responses to the paired associates were significantly (p < 0.01) correlated at the single-neuron level ("pair-coding neuron") dramatically increased from TE (4.9% of the cue-selective neurons) to A36 (33%). The pair-coding neurons in A36 were further separable into Type1 (68%) and Type2 (32%) on the basis of their initial transient responses after cue stimulus presentation. Type1 neurons, but not Type2 neurons, began to encode association between paired stimuli as soon as they exhibited stimulus selectivity. Thus, the representation of long-term memory encoded by Type1 neurons in A36 is likely substantiated without feedback input from other higher centers. Therefore, we conclude that association between the representations of the paired associates proceeds forward at this critical step within IT cortex, suggesting selective convergence onto a single A36 neuron from two TE neurons that encode separate visual objects.

Inherent in visual scene analysis is a bottleneck associated with the need to sequentially sample locations with foveating eye movements. The concept of a ‘saliency map’ topographically encoding stimulus conspicuity over the visual scene has proven to be an efficient predictor of eye movements. Our work reviews insights into the neurobiological implementation of visual salience computation. We start by summarizing the role that different visual brain areas play in salience computation, whether at the level of feature analysis for bottom-up salience or at the level of goal-directed priority maps for output behaviour. We then delve into how a subcortical structure, the superior colliculus (SC), participates in salience computation. The SC represents a visual saliency map via a centre-surround inhibition mechanism in the superficial layers, which feeds into priority selection mechanisms in the deeper layers, thereby affecting saccadic and microsaccadic eye movements. Lateral interactions in the local SC circuit are particularly important for controlling active populations of neurons. This, in turn, might help explain long-range effects, such as those of peripheral cues on tiny microsaccades. Finally, we show how a combination of in vitro neurophysiology and large-scale computational modelling is able to clarify how salience computation is implemented in the local circuit of the SC.This article is part of the themed issue ‘Auditory and visual scene analysis’.