Interacting rhythms enhance sensitivity of target detection in a fronto-parietal computational model of visual attention

Even during sustained attention, enhanced processing of attended stimuli waxes and wanes rhythmically, with periods of enhanced and relatively diminished visual processing (and hit rates) alternating at 4 or 8 Hz in a sustained visual attention task. These alternating attentional states occur alongside alternating dynamical states, in which lateral intraparietal cortex (LIP), the frontal eye field (FEF), and the mediodorsal pulvinar exhibit different activity and connectivity at α, β, and γ frequencies - rhythms associated with visual processing, working memory, and motor suppression. To assess whether and how these multiple interacting rhythms contribute to periodicity in attention, we propose a detailed computational model of FEF and LIP that reproduces the rhythmic dynamics and behavioral consequences of observed attentional states, when driven by θ-rhythmic inputs simulating experimentally-observed pulvinar activity. This model reveals that the frequencies and mechanisms of the observed rhythms optimize sensitivity in visual target detection while maintaining functional flexibility.

Pseudosparse neural coding in the visual system of primates

When measuring sparseness in neural populations as an indicator of efficient coding, an implicit assumption is that each stimulus activates a different random set of neurons. In other words, population responses to different stimuli are, on average, uncorrelated. Here we examine neurophysiological data from four lobes of macaque monkey cortex, including V1, V2, MT, anterior inferotemporal cortex, lateral intraparietal cortex, the frontal eye fields, and perirhinal cortex, to determine how correlated population responses are. We call the mean correlation the pseudosparseness index, because high pseudosparseness can mimic statistical properties of sparseness without being authentically sparse. In every data set we find high levels of pseudosparseness ranging from 0.59–0.98, substantially greater than the value of 0.00 for authentic sparseness. This was true for synthetic and natural stimuli, as well as for single-electrode and multielectrode data. A model indicates that a key variable producing high pseudosparseness is the standard deviation of spontaneous activity across the population. Consistently high values of pseudosparseness in the data demand reconsideration of the sparse coding literature as well as consideration of the degree to which authentic sparseness provides a useful framework for understanding neural coding in the cortex.

Neuronal Correlates of Many-To-One Sensorimotor Mapping in Lateral Intraparietal Cortex

Efficiently mapping sensory stimuli onto motor programs is crucial for rapidly choosing appropriate behavioral responses. While neuronal mechanisms underlying simple, one-to-one sensorimotor mapping have been extensively studied, how the brain achieves complex, many-to-one sensorimotor mapping remains unclear. Here, we recorded single neuron activity from the lateral intraparietal (LIP) cortex of monkeys trained to map multiple spatial positions of visual cue onto two opposite saccades. We found that LIP neurons’ activity was consistent with directly mapping multiple cue positions to the associated saccadic direction (SDir) regardless of whether the visual cue appeared in or outside neurons’ receptive fields. Unlike the explicit encoding of the visual categories, such cue–target mapping (CTM)–related activity covaried with the associated SDirs. Furthermore, the CTM was preferentially mediated by visual neurons identified by memory-guided saccade. These results indicate that LIP plays a crucial role in the early stage of many-to-one sensorimotor transformation.

Perceptual modulation of parietal activity during urgent saccadic choices

The lateral intraparietal cortex (LIP) contributes to visuomotor transformations for determining where to look next. However, its spatial selectivity can signify attentional priority, motor planning, perceptual discrimination, or other mechanisms. Resolving how this LIP signal influences a perceptually guided choice requires knowing exactly when such signal arises and when the perceptual evaluation informs behavior. To achieve this, we recorded single-neuron activity while monkeys performed an urgent choice task for which the perceptual evaluation’s progress can be tracked millisecond by millisecond. The evoked presaccadic responses were strong, exhibited modest motor preference, and were only weakly modulated by sensory evidence. This modulation was remarkable, though, in that its time course preceded and paralleled that of behavioral performance (choice accuracy), and it closely resembled the statistical definition of confidence. The results indicate that, as the choice process unfolds, LIP dynamically combines attentional, motor, and perceptual signals, the former being much stronger than the latter.

The effect of context on sensory accumulation involved in decision-making

The underlying processes allowing for decision-making has been a question of interest for many neuroscientists. The lateral intraparietal cortex, or LIP, was shown to accumulate context and sensory information to compute a decision variable. The following review will present the work of Kumano, Suda and Uka who studied the link between context and sensory information during decision-making. To do so, a monkey was trained to associate the color of a fixating dot to one of two tasks. The tasks consisted in either indicating the motion or the depth of themajority of the dots on a screen. The local field potential of the LIP neurons was recorded, and the researchers found a role of context during the stimulus presentation in regards to decision formation. The results have important implication for mental disorders involving malfunction in decision processes.

Rate fluctuations not steps dominate LIP activity during decision-making

The idea that lateral intraparietal cortex (LIP) integrates information for and against a decision, is one of the most popular models in neuroscience. However, a recent statistical analysis has suggested that LIP does not integrate information but that individual neurons’ activities jump. The result was based on a model comparison, which is often hard to interpret. There are two worries that can render comparisons problematic. (1) Important aspects of variance are contained in neither model. (2) The analysis is complicated, making it hard to verify. We thus followed up with a simple approach for model comparison: crossvalidation. We find evidence that baseline fluctuations describe much of the variance, which are properly modeled by neither the original paper’s drift-diffusion model, nor simple ramp or step models. Moreover, we find that our straightforward analysis strategy prefers ramping models, both with and without trial-by-trial baseline fluctuations. Our analysis, implementable in a few lines of code, suggests the importance of simple analyses.

Intrinsic neuronal dynamics predict distinct functional roles during working memory

Working memory (WM) is characterized by the ability to maintain stable representations over time; however, neural activity associated with WM maintenance can be highly dynamic. We explore whether complex population coding dynamics during WM relate to the intrinsic temporal properties of single neurons in lateral prefrontal cortex (lPFC), the frontal eye fields (FEF) and lateral intraparietal cortex (LIP) of two monkeys (Macaca mulatta). We found that cells with short timescales carried memory information relatively early during memory encoding in lPFC; whereas long timescale cells played a greater role later during processing, dominating coding in the delay period. We also observed a link between functional connectivity at rest and intrinsic timescale in FEF and LIP. Our results indicate that individual differences in the temporal processing capacity predicts complex neuronal dynamics during WM; ranging from rapid dynamic encoding of stimuli to slower, but stable, maintenance of mnemonic information.

Cause for pause before leaping to conclusions about stepping

Many neurons in parietal and prefrontal association cortex undergo gradual changes in firing rate during the formation of some perceptual decisions. These dynamics are often ramp-like increases or decreases depending on the sign and strength of the sensory evidence and are thus hypothesized to represent the accumulation of noisy samples of evidence, analogous to biased diffusion. This idea was challenged recently. An analysis of sequences of action potentials recorded from neurons in the lateral intraparietal cortex (area LIP) suggests that the spikes on single trials are explained by rates that undergo a discrete step from an intermediate rate to either a low or high rate at a random time during deliberation. The average of such steps, like the average of biased diffusion, is consistent with the ramp-like firing rates observed in LIP, but a Bayesian model comparison deemed stepping superior. Here we show that a shortcoming in the mathematical depiction of drift-diffusion led to a severe bias in the model comparison. We conclude that at present there is no compelling evidence that favors the stepping account.

Two subdivisions of macaque LIP process visual-oculomotor information differently

Although the cerebral cortex is thought to be composed of functionally distinct areas, the actual parcellation of area and assignment of function are still highly controversial. An example is the much-studied lateral intraparietal cortex (LIP). Despite the general agreement that LIP plays an important role in visual-oculomotor transformation, it remains unclear whether the area is primary sensory- or motor-related (the attention-intention debate). Although LIP has been considered as a functionally unitary area, its dorsal (LIPd) and ventral (LIPv) parts differ in local morphology and long-distance connectivity. In particular, LIPv has much stronger connections with two oculomotor centers, the frontal eye field and the deep layers of the superior colliculus, than does LIPd. Such anatomical distinctions imply that compared with LIPd, LIPv might be more involved in oculomotor processing. We tested this hypothesis physiologically with a memory saccade task and a gap saccade task. We found that LIP neurons with persistent memory activities in memory saccade are primarily provoked either by visual stimulation (vision-related) or by both visual and saccadic events (vision-saccade–related) in gap saccade. The distribution changes from predominantly vision-related to predominantly vision-saccade–related as the recording depth increases along the dorsal-ventral dimension. Consistently, the simultaneously recorded local field potential also changes from visual evoked to saccade evoked. Finally, local injection of muscimol (GABA agonist) in LIPv, but not in LIPd, dramatically decreases the proportion of express saccades. With these results, we conclude that LIPd and LIPv are more involved in visual and visual-saccadic processing, respectively.