Neural dynamics of causal inference in the macaque frontoparietal circuit

ABSTRACTNatural perception relies inherently on inferring causal structure in the environment. However, the neural mechanisms and functional circuits that are essential for representing and updating the hidden causal structure and corresponding sensory representations during multisensory processing are unknown. To address this, monkeys were trained to infer the probability of a potential common source from visual and proprioceptive signals on the basis of their spatial disparity in a virtual reality system. The proprioceptive drift reported by monkeys demonstrated that they combined historical information and current multisensory signals to estimate the hidden common source and subsequently updated both the causal structure and sensory representation. Single-unit recordings in premotor and parietal cortices revealed that neural activity in premotor cortex represents the core computation of causal inference, characterizing the estimation and update of the likelihood of integrating multiple sensory inputs at a trial-by-trial level. In response to signals from premotor cortex, neural activity in parietal cortex also represents the causal structure and further dynamically updates the sensory representation to maintain consistency with the causal inference structure. Thus, our results indicate how premotor cortex integrates historical information and sensory inputs to infer hidden variables and selectively updates sensory representations in parietal cortex to support behavior. This dynamic loop of frontal-parietal interactions in the causal inference framework may provide the neural mechanism to answer long-standing questions regarding how neural circuits represent hidden structures for body-awareness and agency.

A Role for Visual Areas in Physics Simulations

To engage with the world, we must regularly make predictions about the outcomes of physical scenes. How do we make these predictions? Recent evidence points to simulation - the idea that we can introspectively manipulate rich, mental models of the world - as one possible explanation for how such predictions are accomplished. While theories based on simulation are supported by computational models, neuroscientific evidence for simulation is lacking and many important questions remain. For instance, do simulations simply entail a series of abstract computations? Or are they supported by sensory representations of the objects that comprise the scene being simulated? We posit the latter and suggest that the process of simulating a sequence of physical interactions is likely to evoke an imagery-like envisioning of those interactions. Using functional magnetic resonance imaging, we demonstrate that when participants predict how a ball will fall through an obstacle-filled display, motion-sensitive brain regions are activated. We further demonstrate that this activity, which occurs even though no motion is being sensed, resembles activity patterns that arise while participants perceive the ball's motion. This finding suggests that the process of simulating the ball's movement is accompanied by a sensory representation of this movement. These data thus demonstrate that mental simulations recreate sensory depictions of how a physical scene is likely to unfold.

The Naturalizing Program of Perceptions Defended

The author defends the naturalizing program of the notion of representation against the primitivist view according to which the notion of representation as belonging to psychology as a mature science is irreducible. First, the author concedes that the original teleological project trivializes the concept of representation by applying it to bacteria, protozoa, amoeba, when the best available explanation is the assumption that primitive organisms and artifacts are merely indicating proximal stimulation rather than representing the distal causes of stimulation. Yet, the author does not believe that this presents an unsurmountable obstacle for the naturalizing program when what is in question is genuine sensory representation, namely perception. In the author’s view, what matters for the naturalizing program are not cases in which the concept of representation is misemployed, but rather cases in which the focus is genuine sensory representation, that is, genuine perceptions; or so he shall argue.

Connectivity patterns shape sensory representation in a cerebellum-like network

SUMMARYCerebellum-like structures are found in many brains and share a basic fan-out–fan-in network architecture. How the specific structural features of these networks give rise to their learning function remains largely unknown. To investigate this structure–function relationship, we developed a realistic computational model of an empirically very well-characterized cerebellum-like structure, the Drosophila melanogaster mushroom body. We show how well-defined connectivity patterns between the Kenyon cells, the constituent neurons of the mushroom body, and their input projection neurons enable different functions. First, biases in the likelihoods at which individual projection neurons connect to Kenyon cells allow the mushroom body to prioritize the learning of particular, ethologically meaningful odors. Second, groups of projection neurons connecting preferentially to the same Kenyon cells facilitate the mushroom body generalizing across similar odors. Altogether, our results demonstrate how different connectivity patterns shape the representation space of a cerebellum-like network and impact its learning outcomes.

Neural mechanisms underlying expectation-dependent inhibition of distracting information

Predictions based on learned statistical regularities in the visual world have been shown to facilitate attention and goal-directed behavior by sharpening the sensory representation of goal-relevant stimuli in advance. Yet, how the brain learns to ignore predictable goal-irrelevant or distracting information is unclear. Here, we used EEG and a visual search task in which the predictability of a distractor’s location and/or spatial frequency was manipulated to determine how spatial and feature distractor expectations are neurally implemented and reduce distractor interference. We find that expected distractor features could not only be decoded pre-stimulus, but their representation differed from the representation of that same feature when part of the target. Spatial distractor expectations did not induce changes in preparatory neural activity, but a strongly reduced Pd, an ERP index of inhibition. These results demonstrate that neural effects of statistical learning critically depend on the task relevance and dimension (spatial, feature) of predictions.

Neural mechanisms underlying expectation-dependent inhibition of distracting information

Predictions based on learned statistical regularities in the visual world have been shown to facilitate attention and goal-directed behavior by sharpening the sensory representation of goal-relevant stimuli in advance. Yet, how the brain learns to ignore predictable goal-irrelevant or distracting information is unclear. Here, we used EEG and a visual search task in which the predictability of a distractor’s location and/or spatial frequency was manipulated to determine how spatial and feature distractor expectations are neurally implemented and reduce distractor interference. We find that expected distractor features could not only be decoded pre-stimulus, but their representation differed from the representation of that same feature when part of the target. Spatial distractor expectations did not induce changes in preparatory neural activity, but a strongly reduced Pd, an ERP index of inhibition. These results demonstrate that neural effects of statistical learning critically depend on the task relevance and dimension (spatial, feature) of predictions.

Expressive component of the interpreter’s emotional response in consecutive interpreting

The article highlights the main issues of consecutive bilateral interpretation from the point of view psycholinguistics and translation studies. The daily translation is a well-established, ordinary, new terminology, which is translated according to a one-sided (sequential) model. The lexical stock of the translator is characterized as a complex system of language units, where the important place is occupied by functional words that serve as connecting or expressive elements in semantic units-phrases and sentences. The communicative process, which is performed according to its status of the language level has analyzed. Varieties of the speaker’s language have distinguished in translation practice. The concept of oral and consecutive translation has substantiated. The sign system of communication has developed. Praxemics has considered as one of the areas of psychology in the study of nonverbal communication, that is covering the doctrine of touch, kinesics, time structure. The physiological basis of the translator’s perception has revealed. The translator is a person who constantly interacts with the world around him. Any act of such interaction is based on the sensory representation of its immediate environment, which includes general orientation, assessment of the location relevant objects, their physical properties, situational significance, behavioral, symbolic or aesthetic content. The concept of „primary information” has formulated, which serves as a source for the emergence and functioning of higher forms of mental activity that is going beyond the immediate given and provide regulation of various oriented, cognitive, practical activities (locomotion, problem solving, social communication or labor operations etc.).

Stimulus-choice (mis)alignment in primate MT cortex

For stimuli near perceptual threshold, the trial-by-trial activity of single neurons in many sensory areas is correlated with the animal’s perceptual report. This phenomenon has often been attributed to feedforward readout of the neural activity by the downstream decision-making circuits. The interpretation of choice-correlated activity is quite ambiguous, but its meaning can be better understood in the light of population-wide correlations among sensory neurons. Using a statistical nonlinear dimensionality reduction technique on single-trial ensemble recordings from the middle temporal area during perceptual-decision-making, we extracted low-dimensional neural tra jectories that captured the population-wide fluctuations. We dissected the particular contributions of sensory-driven versus choice-correlated activity in the low-dimensional population code. We found that the neural trajectories strongly encoded the direction of the stimulus in single dimension with a temporal signature similar to that of single MT neurons. If the downstream circuit were optimally utilizing this information, choice-correlated signals should be aligned with this stimulus encoding dimension. Surprisingly, we found that a large component of the choice information resides in the subspace orthogonal to the stimulus representation inconsistent with the optimal readout view. This misaligned choice information allows the feedforward sensory information to coexist with the decision-making process. The time course of these signals suggest that this misaligned contribution likely is feedback from the downstream areas. We hypothesize that this non-corrupting choice-correlated feedback might be related to learning or reinforcing sensory-motor relations in the sensory population.Author summaryIn sensorimotor decision-making, internal representation of sensory stimuli is utilized for the generation of appropriate behavior for the context. Therefore, the correlation between variability in sensory neurons and perceptual decisions is sometimes explained by a causal, feedforward role of sensory noise in behavior. However, this correlation could also originate via feedback from decision-making mechanisms downstream of the sensory representation. This cannot be resolved by analyzing single unit responses, but requires a population level analysis. Area MT contains both sensory and choice information and is known to be the key sensory area for visual motion perception. Thus the decision-making process may be corrupting the sensory representation. However, we find that the sensory stimuli and choice variables are separate at the population level,contradicting the previous interpretations based on single unit recordings. This new insight postulates how neural systems can maintain a mixed representation while allows learning and adaptation.