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Erez, Y.

Publications and source records attributed to Erez, Y..

4 recordsLinked to original sources

Prefrontal neural dynamics for behavioral decisions and attentional control

Complex neural dynamics in the prefrontal cortex contribute to context-dependent decisions and attentional competition. To analyze these dynamics, we apply demixed principal component analysis to activity of a primate prefrontal cell sample recorded in a cued target detection task. The results track dynamics of cue and object coding, feeding into movements along a target present-absent decision axis in a low-dimensional subspace of population activity. For a single stimulus, object and cue coding are seen mainly in the contralateral hemisphere. Later, a developing decision code in both hemispheres may reflect interhemispheric communication. With a target in one hemifield and a competing nontarget in the other, each hemisphere initially encodes the contralateral object, but finally, decision coding is dominated by the task-relevant target. These findings further suggest that exchange of information between hemispheres plays a key role when attentional competition resolves. Tracking complex neural events in a low-dimensional activity subspace illuminates integration of neural codes towards task-appropriate behavior, comprising a building block of learned task structure in the prefrontal cortex. AUTHOR SUMMARYFlexible adaptive processing of information is integral for everyday goal-directed behavior. To unravel dynamic representation of task-relevant information, we analyzed population activity of a primate prefrontal cell sample in a cued target detection task. In a low-dimensional neural subspace, with separate axes for cue, object identity and decision, trajectories showed initial coding of cue and object in the contralateral hemisphere, followed by coding of the behavioral decision across both hemispheres. With target and nontarget stimuli in opposite hemifields, the data suggest initial coding of the contralateral object in each hemisphere. Object coding is then rapidly shut off for the nontarget, and followed by bilateral coding of the target decision. The results bring detailed insight into task structure and information flow within and between the two frontal lobes as a decision is made and attentional competition is resolved.

neuroscience↗

Localizing the multiple-demand frontoparietal network in individual subjects

The frontoparietal multiple-demand (MD) control network plays a key role in goal-directed behavior. Recent developments of multivoxel pattern analysis (MVPA) for fMRI data allow for more fine-grained investigations into the functionality and properties of brain systems. In particular, MVPA in the MD network was used to gain better understanding of control processes such as attentional effects, adaptive coding, and representation of multiple task-relevant features, but overall low decoding levels have limited its use for this network. A common practice of applying MVPA is by investigating pattern discriminability within a region-of-interest (ROI) using a template mask, thus ensuring that the same brain areas are studied in all participants. This approach offers high sensitivity, but does not take into account differences between individuals in the spatial organization of brain regions. An alternative approach uses independent localizer data for each subject to select the most responsive voxels and define individual ROIs within the boundaries of a group template. Such an approach allows for a refined and targeted localization based on the unique pattern of activity of individual subjects while ensuring that functionally similar brain regions are studied for all subjects. In the current study we tested whether using individual ROIs leads to changes in decodability of task-related neural representations as well as univariate activity across the MD network compared to when using a group template. We used three localizer tasks to separately define subject-specific ROIs: spatial working memory, verbal working memory, and a Stroop task. We then systematically assessed univariate and multivariate results in a separate rule-based criterion task. All the localizer tasks robustly recruited the MD network and evoked highly reliable activity patterns in individual subjects. Consistent with previous studies, we found a clear benefit of the subject-specific ROIs for univariate results from the criterion task, with increased activity in the individual ROIs based on the localizers data, compared to the activity observed when using the group template. In contrast, there was no benefit of the subject-specific ROIs for the multivariate results in the form of increased discriminability, as well as no cost of reduced discriminability. Both univariate and multivariate results were similar in the subject-specific ROIs defined by each of the three localizers. Our results provide important empirical evidence for researchers in the field of cognitive control for the use of individual ROIs in the frontoparietal network for both univariate and multivariate analysis of fMRI data, and serve as another step towards standardization and increased comparability across studies.

neuroscience↗

Reward motivation modulates representation of behaviorally-relevant information across the frontoparietal cortex

Selection and integration of information based on current goals is fundamental for goal-directed behavior. Reward motivation has been shown to improve behavioral performance, yet the neural mechanisms that link motivation and control processes, and in particular its effect on context-dependent information processing, remain unclear. We used functional magnetic resonance imaging (fMRI) in 24 human volunteers (13 females) to test whether reward motivation enhances the coding of task-relevant information across the frontoparietal cortex, as would be predicted based on previous experimental evidence and theoretical accounts. In a cued target detection task, participants detected whether an object from a cued visual category was present in a subsequent display. The combination of the cue and the object visual category determined the behavioral status of the objects. To manipulate reward motivation, half of all trials offered the possibility of a monetary reward. We observed an increase with reward in overall univariate activity across the frontoparietal control network when the cue and subsequent object were presented. Multivariate pattern analysis (MVPA) showed that behavioral status information for the objects was conveyed across the network. However, in contrast to our prediction, reward did not increase the discrimination between behavioral status conditions in the stimulus epoch of a trial when object information was processed depending on a current context. In the high-level general-object visual region, the lateral occipital complex, the representation of behavioral status was driven by visual differences and was not modulated by reward. Our study provides useful evidence for the limited effects of reward motivation on task-related neural representations and highlights the necessity to unravel the diverse forms and extent of these effects.

neuroscience↗

The processing of dynamic faces in the human brain: Support for an integrated neural framework of face processing.

Faces convey rich information including identity, gender and expression. Current neural models of face processing suggest a dissociation between the processing of invariant facial aspects such as identity and gender, that engage the fusiform face area (FFA) and the processing of changeable aspects, such as expression and eye gaze, that engage the posterior superior temporal sulcus face area (pSTS-FA). Recent studies report a second dissociation within this network such that the pSTS-FA, but not the FFA, shows much stronger response to dynamic than static faces. The aim of the current study was to test a unified model that accounts for these two major functional characteristics of the neural face network. In an fMRI experiment, we presented static and dynamic faces while subjects judged an invariant (gender) or a changeable facial aspect (expression). We found that the pSTS-FA was more engaged in processing dynamic than static faces and changeable than invariant facial aspects, whereas the OFA and FFA showed similar response across all four conditions. Our results reveal no dissociation between the processing of changeable and invariant facial aspects, but higher sensitivity to the processing of changeable facial aspects by the motion-sensitive face area in the superior temporal sulcus.

neuroscience↗