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Wardak, C.

Publications and source records attributed to Wardak, C..

5 recordsLinked to original sources

Distinct neural states encode task identity in frontal eye field and interact with its core spatial properties

The prefrontal cortex (PFC) plays a key role in selecting, maintaining and representing sensory information, and in its integration with our current internal goals and expectations, implementing such cognitive processes as executive functions, attention, decision making and working memory. Performing computation over all of these functional cognitive processes and dynamically shifting from one to the other based on task demands requires a complex functional organization and a high degree of coding flexibility. The PFC cells show a non-linear mixed selectivity characterized by specific tuning for multiple task- and behaviour related parameters. This non-linear mixed selectivity thought to allow for a high-dimensional representation of information. Here, we asked if the PFC is mainly involved in specific task-parameters representation, or if it additionally holds a higher order representation for task-identity. We thus trained two macaques to perform three different tasks: a memory guided saccade task and two detection tasks involving different attention mechanisms. Multi-unit activity was recorded in the frontal eye field, bilaterally, while monkeys performed these three tasks in a same session. Using demixed Principal Component Analysis, we found a two-dimensional neural state that characterized each of these tasks. The lower dimensional representation of the activity recorded during the performance of the two attentional tasks were more similar to each other than to the memory-guided saccade task. Furthermore, we report that task and spatial information are non-linearly mixed, a signature of a high-dimensional neural representation. Overall, this indicates that PFC encodes task identity information and flexibly adjusts its sensory processes as a function of the specific ongoing task. Significance StatementOne long lasting question in cognitive neuroscience is whether PFC mainly represents the different parameters that are needed to perform any given task, or if it additionally holds a higher order representation for task-identity. We recorded from the macaque frontal eye fields while monkeys performed a memory guided saccade task and two detection tasks involving different attention mechanisms. We found a task-identity neural state in which the two attentional tasks were represented similarly to each other but differently from the memory-guided saccade task. We also report that task and spatial information are non-linearly mixed, a signature of a high-dimensional neuronal representation. Overall, this indicates that PFC encodes task identity information and flexibly adjusts its sensory processes as a function of the specific ongoing task.

neuroscience↗

Rhythmic variations in prefrontal inter-neuronal correlations, their underlying mechanisms and their behavioral correlates

Functional neuronal correlations between pairs of neurons are thought to play an important role in neuronal information processing and optimal neuronal computations during attention, perception, decision-making and learning. These noise correlations are often assumed to be stable in time. However, recent studies suggest that cognitive processes are rhythmic, this rhythmicity accounting for variations in overt behavioral performance. Whether this rhythmicity coincides with variations in shared noise variability is unknown. Here, we perform simultaneous recordings from the macaque frontal eye fields, while animals are engaged in a spatial memory task. We report that noise correlations in prefrontal cortex fluctuate rhythmically in the high alpha (10-16Hz) and beta (20-30Hz) frequency ranges. Importantly, these rhythmic modulations in shared neuronal variability account for dynamic changes in overt behavioral performance. They also coincide with increased spike-LFP phase coupling in these specific frequency ranges, the spatial profile of which vary between superficial and deep cortical layers. Finally, we demonstrate, using an artificial neuronal model, that rhythmic variations in noise correlation oscillations parsimoniously arise from long range (LFP) and local spike-LFP phase coupling mechanisms. Thus a significant portion of noise correlation fluctuations can be attributed to long-range global network rhythmicity.

neuroscience↗

Interneuronal correlations dynamically adjust to task demands at multiple time-scales

Functional neuronal correlations between pairs of neurons are thought to play an important role in neuronal information processing and optimal neuronal computations during attention, perception, decision-making and learning. Here, we report dynamic changes in prefrontal neuronal noise correlations at multiple time-scales, as a function of task contingencies. Specifically, we record neuronal activity from the macaque frontal eye fields, a cortical region at the source of spatial attention top-down control, while the animals are engaged in tasks of varying cognitive demands. First, we show that noise correlations decrease as cognitive engagement and task demands increase, both across tasks and within-trials. Second, we demonstrate, for the first time, rhythmic modulations of noise correlations in the alpha and beta frequency ranges that account both for overt behavioral performance and for layer specific modulations in spike-field coherence. All this taken together demonstrates a strong functional role of noise correlations in cognitive flexibility.

neuroscience↗

Neuronal population correlates of target selection and distractor filtering

Frontal Eye Field (FEF) single-cell neuronal activity discriminates between relevant and irrelevant visual stimuli and its magnitude has been shown to predict conscious perception. How this is reflected at the population level in terms of spatial codes is unknown. We recorded neuronal population activity in the FEF while monkeys were performing a forced choice cued detection task with identical target and distractor stimuli. Using machine learning techniques, we quantified information about the spatial estimate of targets and distracters in the FEF population activity and we analyzed how these relate to the report of perception. We found that the FEF population activity provides a precise estimate of the spatial location of perception. This estimate doesnt necessarily match the actual physical world. Importantly, the closer this prefrontal population estimate is to the veridical spatial information, the higher the probability that the stimulus was reported as perceived. This was observed both when the reported stimulus was a target (i.e. correct detection trials) or a distractor (i.e. false alarm trials). Overall, we thus show that how and what we perceive of our environments depends on the precision with which this environment is coded by prefrontal neuronal populations.

neuroscience↗

Cortical networks for encoding near and far space in the non-human primate

While extra-personal space is often erroneously considered as a unique entity, early neuropsychological studies report a dissociation between near and far space processing both in humans and in monkeys. Here, we use functional MRI in a naturalistic 3D environment to describe the non-human primate near and far space cortical networks. We describe the co-occurrence of two extended functional networks respectively dedicated to near and far space processing. Specifically, far space processing involves occipital, temporal, parietal, posterior cingulate as well as orbitofrontal regions not activated by near space, possibly subserving the processing of the shape and identity of objects. In contrast, near space processing involves temporal, parietal and prefrontal regions not activated by far space, possibly subserving the preparation of an arm/hand mediated action in this proximal space. Interestingly, this network also involves somatosensory regions, suggesting a cross-modal anticipation of touch by a nearby object. Last, we also describe cortical regions that process both far and near space with a preference for one or the other. This suggests a continuous encoding of relative distance to the body, in the form of a far-to-near gradient. We propose that these cortical gradients in space representation subserve the physically delineable peripersonal spaces described in numerous psychology and psychophysics studies.\n\nHighlightsO_LINear space processing involves temporal, parietal and prefrontal regions.\nC_LIO_LIFar space activates occipital, temporal, parietal, cingulate & orbitofrontal areas.\nC_LIO_LIMost regions process both far & near space, with a preference for one or the other.\nC_LIO_LIFar-to-near gradient may subserve behavioral changes in peripersonal space size.\nC_LI

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