Human Frontoparietal Cortex Research Articles

Visuomotor prediction during action planning in the human frontoparietal cortex and cerebellum.

The concept of forward models in the brain, classically applied to describing on-line motor control, can in principle be extended to action planning, i.e. assuming forward sensory predictions are issued during the mere preparation of movements. To test this idea, we combined a delayed movement task with a virtual reality based manipulation of visuomotor congruence during functional magnetic resonance imaging. Participants executed simple hand movements after a delay. During the delay, two aspects of the upcoming movement could be cued: the movement type and the visuomotor mapping (i.e. congruence of executed hand movements and visual movement feedback by a glove-controlled virtual hand). Frontoparietal areas showed increased delay period activity when preparing pre-specified movements (cued > uncued). The cerebellum showed increased activity during the preparation for incongruent > congruent visuomotor mappings. The left anterior intraparietal sulcus showed an interaction effect, responding most strongly when a pre-specified (cued) movement was prepared under expected visuomotor incongruence. These results suggest that motor planning entails a forward prediction of visual body movement feedback, which can be adjusted in anticipation of nonstandard visuomotor mappings, and which is likely computed by the cerebellum and integrated with state estimates for (planned) control in the anterior intraparietal sulcus.

Adaptive coding of stimulus information in human frontoparietal cortex during visual classification

The neural mechanisms of how frontal and parietal brain regions support flexible adaptation of behavior remain poorly understood. Here, we used functional magnetic resonance imaging (fMRI) and representational similarity analysis (RSA) to investigate frontoparietal representations of stimulus information during visual classification under varying task demands. Based on prior research, we predicted that increasing perceptual task difficulty should lead to adaptive changes in stimulus coding: task-relevant category information should be stronger, while task-irrelevant exemplar-level stimulus information should become weaker, reflecting a focus on the behaviorally relevant category information. Counter to our expectations, however, we found no evidence for adaptive changes in category coding. We did find weakened coding at the exemplar-level within categories however, demonstrating that task-irrelevant information is de-emphasized in frontoparietal cortex. These findings reveal adaptive coding of stimulus information at the exemplar-level, highlighting how frontoparietal regions might support behavior even under challenging conditions.

Human frontoparietal cortex represents behaviorally relevant target status based on abstract object features.

Searching for items that are useful given current goals, or "target" recognition, requires observers to flexibly attend to certain object properties at the expense of others. This could involve focusing on the identity of an object while ignoring identity-preserving transformations such as changes in viewpoint or focusing on its current viewpoint while ignoring its identity. To effectively filter out variation due to the irrelevant dimension, performing either type of task is likely to require high-level, abstract search templates. Past work has found target recognition signals in areas of ventral visual cortex and in subregions of parietal and frontal cortex. However, target status in these tasks is typically associated with the identity of an object, rather than identity-orthogonal properties such as object viewpoint. In this study, we used a task that required subjects to identify novel object stimuli as targets according to either identity or viewpoint, each of which was not predictable from low-level properties such as shape. We performed functional MRI in human subjects of both sexes and measured the strength of target-match signals in areas of visual, parietal, and frontal cortex. Our multivariate analyses suggest that the multiple-demand (MD) network, including subregions of parietal and frontal cortex, encodes information about an object's status as a target in the relevant dimension only, across changes in the irrelevant dimension. Furthermore, there was more target-related information in MD regions on correct compared with incorrect trials, suggesting a strong link between MD target signals and behavior. NEW & NOTEWORTHY Real-world target detection tasks, such as searching for a car in a crowded parking lot, require both flexibility and abstraction. We investigated the neural basis of these abilities using a task that required invariant representations of either object identity or viewpoint. Multivariate decoding analyses of our whole brain functional MRI data reveal that invariant target representations are most pronounced in frontal and parietal regions, and the strength of these representations is associated with behavioral performance.

Representations of time in human frontoparietal cortex

Precise time estimation is crucial in perception, action and social interaction. Previous neuroimaging studies in humans indicate that perceptual timing tasks involve multiple brain regions; however, whether the representation of time is localized or distributed in the brain remains elusive. Using ultra-high-field functional magnetic resonance imaging combined with multivariate pattern analyses, we show that duration information is decoded in multiple brain areas, including the bilateral parietal cortex, right inferior frontal gyrus and, albeit less clearly, the medial frontal cortex. Individual differences in the duration judgment accuracy were positively correlated with the decoding accuracy of duration in the right parietal cortex, suggesting that individuals with a better timing performance represent duration information in a more distinctive manner. Our study demonstrates that although time representation is widely distributed across frontoparietal regions, neural populations in the right parietal cortex play a crucial role in time estimation.

Continuous vs. categorical representation of feature-based attentional priority in human frontoparietal cortex

Continuous vs. categorical representation of feature-based attentional priority in human frontoparietal cortex

Visual field map clusters in human frontoparietal cortex.

The visual neurosciences have made enormous progress in recent decades, in part because of the ability to drive visual areas by their sensory inputs, allowing researchers to define visual areas reliably across individuals and across species. Similar strategies for parcellating higher-order cortex have proven elusive. Here, using a novel experimental task and nonlinear population receptive field modeling, we map and characterize the topographic organization of several regions in human frontoparietal cortex. We discover representations of both polar angle and eccentricity that are organized into clusters, similar to visual cortex, where multiple gradients of polar angle of the contralateral visual field share a confluent fovea. This is striking because neural activity in frontoparietal cortex is believed to reflect higher-order cognitive functions rather than external sensory processing. Perhaps the spatial topography in frontoparietal cortex parallels the retinotopic organization of sensory cortex to enable an efficient interface between perception and higher-order cognitive processes. Critically, these visual maps constitute well-defined anatomical units that future studies of frontoparietal cortex can reliably target.

Attentional priority signals in human frontoparietal cortex correlate with performance in a feature-based attention task

Attentional priority signals in human frontoparietal cortex correlate with performance in a feature-based attention task

Feature-Selective Attentional Modulations in Human Frontoparietal Cortex

Control over visual selection has long been framed in terms of a dichotomy between "source" and "site," where top-down feedback signals originating in frontoparietal cortical areas modulate or bias sensory processing in posterior visual areas. This distinction is motivated in part by observations that frontoparietal cortical areas encode task-level variables (e.g., what stimulus is currently relevant or what motor outputs are appropriate), while posterior sensory areas encode continuous or analog feature representations. Here, we present evidence that challenges this distinction. We used fMRI, a roving searchlight analysis, and an inverted encoding model to examine representations of an elementary feature property (orientation) across the entire human cortical sheet while participants attended either the orientation or luminance of a peripheral grating. Orientation-selective representations were present in a multitude of visual, parietal, and prefrontal cortical areas, including portions of the medial occipital cortex, the lateral parietal cortex, and the superior precentral sulcus (thought to contain the human homolog of the macaque frontal eye fields). Additionally, representations in many-but not all-of these regions were stronger when participants were instructed to attend orientation relative to luminance. Collectively, these findings challenge models that posit a strict segregation between sources and sites of attentional control on the basis of representational properties by demonstrating that simple feature values are encoded by cortical regions throughout the visual processing hierarchy, and that representations in many of these areas are modulated by attention. Influential models of visual attention posit a distinction between top-down control and bottom-up sensory processing networks. These models are motivated in part by demonstrations showing that frontoparietal cortical areas associated with top-down control represent abstract or categorical stimulus information, while visual areas encode parametric feature information. Here, we show that multivariate activity in human visual, parietal, and frontal cortical areas encode representations of a simple feature property (orientation). Moreover, representations in several (though not all) of these areas were modulated by feature-based attention in a similar fashion. These results provide an important challenge to models that posit dissociable top-down control and sensory processing networks on the basis of representational properties.

Neural Coding for Instruction-Based Task Sets in Human Frontoparietal and Visual Cortex.

Task preparation has traditionally been thought to rely upon persistent representations of instructions that permit their execution after delays. Accumulating evidence suggests, however, that accurate retention of task knowledge can be insufficient for successful performance. Here, we hypothesized that instructed facts would be organized into a task set; a temporary coding scheme that proactively tunes sensorimotor pathways according to instructions to enable highly efficient "reflex-like" performance. We devised a paradigm requiring either implementation or memorization of novel stimulus-response mapping instructions, and used multivoxel pattern analysis of neuroimaging data to compare neural coding of instructions during the pretarget phase. Although participants could retain instructions under both demands, we observed striking differences in their representation. To-be-memorized instructions could only be decoded from mid-occipital and posterior parietal cortices, consistent with previous work on visual short-term memory storage. In contrast, to-be-implemented instructions could also be decoded from frontoparietal "multiple-demand" regions, and dedicated visual areas, implicated in processing instructed stimuli. Neural specificity in the latter moreover correlated with performance speed only when instructions were prepared, likely reflecting the preconfiguration of instructed decision circuits. Together, these data illuminate how the brain proactively optimizes performance, and help dissociate neural mechanisms supporting task control and short-term memory storage.

A hierarchy of attentional priority signals in human frontoparietal cortex.

Humans can voluntarily attend to a variety of visual attributes to serve behavioral goals. Voluntary attention is believed to be controlled by a network of dorsal frontoparietal areas. However, it is unknown how neural signals representing behavioral relevance (attentional priority) for different attributes are organized in this network. Computational studies have suggested that a hierarchical organization reflecting the similarity structure of the task demands provides an efficient and flexible neural representation. Here we examined the structure of attentional priority using functional magnetic resonance imaging. Participants were cued to attend to location, color, or motion direction within the same stimulus. We found a hierarchical structure emerging in frontoparietal areas, such that multivoxel patterns for attending to spatial locations were most distinct from those for attending to features, and the latter were further clustered into different dimensions (color vs motion). These results provide novel evidence for the organization of the attentional control signals at the level of distributed neural activity. The hierarchical organization provides a computationally efficient scheme to support flexible top-down control.

Prioritized Maps of Space in Human Frontoparietal Cortex

Priority maps are theorized to be composed of large populations of neurons organized topographically into a map of gaze-centered space whose activity spatially tags salient and behaviorally relevant information. Here, we identified four priority map candidates along human posterior intraparietal sulcus (IPS0-IPS3) and two along the precentral sulcus (PCS) that contained reliable retinotopically organized maps of contralateral visual space. Persistent activity increased from posterior-to-anterior IPS areas and from inferior-to-superior PCS areas during the maintenance of a working memory representation, the maintenance of covert attention, and the maintenance of a saccade plan. Moreover, decoders trained to predict the locations on one task (e.g., working memory) cross-predicted the locations on other tasks (e.g., attention) in superior PCS and IPS2, suggesting that these patterns of maintenance activity may be interchangeable across the tasks. Such properties make these two areas in frontal and parietal cortex viable priority map candidates.

Metabolic dysfunction and relationship in human frontoparietal cortex in severe traumatic brain injury: Single-voxel 1H magnetic resonance spectroscopy study

(1)H-magnetic resonance spectroscopy revealed that apparently normal (from the data of magnetic resonance imaging) human brain frontoparietal cortex in the subacute stage of traumatic brain injury is characterized by decreased level of N-acetylaspartate (NAA) and increase in levels of myoinositol, choline-containing compounds (Cho), and creatine/phosphocreatine (Cr). Correlations between Cr, Cho, and NAA were established. We propose a scheme of neuronal metabolic processes that joins these substances.

Multi-voxel coding of stimuli, rules, and responses in human frontoparietal cortex

In human functional magnetic resonance imaging (fMRI), a characteristic pattern of frontal and parietal activity is produced by many different cognitive demands. Although frontoparietal cortex has been shown to represent a variety of task features in different contexts, little is known about detailed representation of different task features within and across different regions. We used multi-voxel pattern analysis (MVPA) of human fMRI data to assess the representational content of frontoparietal cortex in a simple stimulus–response task. Stimulus–response mapping rule was the most strongly represented task feature, significantly coded in a lateral frontal region surrounding the inferior frontal sulcus, a more ventral region including the anterior insula/frontal operculum, and the intraparietal sulcus. Next strongest was coding of the instruction cue (screen color) indicating which rule should be applied. Coding of individual stimuli and responses was weaker, approaching significance in a subset of regions. In line with recent single unit data, the results show a broad representation of task-relevant information across human frontoparietal cortex, with strong representation of a general rule or cognitive context, and weaker coding of individual stimulus/response instances.

Tuning to non‐symbolic proportions in the human frontoparietal cortex

Humans share with many species a non-verbal system to estimate absolute quantity. This sense of number has been linked to the activity of quantity-selective neurons that respond maximally to preferred numerosities. With functional magnetic resonance imaging adaptation, we now show that populations of neurons in the human parietal and frontal cortex are also capable of encoding quantity ratios, or proportions, using the same non-verbal analog code as for absolute number. Following adaptation to visually presented constant proportions (specified by the ratio of line lengths or numerosities), we introduced novel relative magnitudes to examine the tuning characteristics of the population of stimulated neurons. In bilateral parietal and frontal cortex we found that blood oxygenation level-dependent signal recovery from adaptation was a function of numerical distance between the deviant proportion and the adaptation stimulus. The strongest effects were observed in the cortex surrounding the anterior intraparietal sulcus, a region considered pivotal for the processing of absolute magnitudes. Overall, there was substantial overlap of frontoparietal structures representing whole numbers and proportions. The identification of tuning to non-symbolic ratio stimuli, irrespective of notation, adds to the magnitude system a remarkable level of sophistication by demonstrating automatic access to a composite, derived quantitative measure. Our results argue that abstract concepts of both absolute and relative number are deeply rooted in the primate brain as fundamental determinants of higher-level numerical cognition.

Attentional modulation of stimulus representation in human fronto-parietal cortex

Evidence from primates suggests that prefrontal and parietal regions selectively represent information that is relevant for current behavior. In humans, whilst functional imaging has shown that fronto-parietal areas are activated by a range of different cognitive demands, the actual content of representation remains unclear. The current report describes two studies designed to address this issue using fMRI adaptation. In both studies, participants completed a delayed matching task where they attended to either the color or the shape of a series of sample stimuli and indicated whether occasional test stimuli matched the preceding sample on the attended dimension. Whole brain contrasts showed that changes to the value of the currently attended dimension produced significantly greater responses in frontal and parietal areas than events where the value was repeated. In addition, prefrontal and parietal regions of interest showed strong interactions between the currently attended dimension and the type of stimulus change, reflecting an attentional modulation of responses to stimulus change. Further comparisons suggested that the differences between attended changes and stimulus repetitions carried information about specific stimulus values, and did not simply reflect a generic response to attended changes.

Notation-Independent Representation of Fractions in the Human Parietal Cortex

Although the concept of whole numbers is intuitive and well suited for counting and ordering, it is with the invention of fractions that the number system gained precision and flexibility. Absolute magnitude is encoded by single neurons that discharge maximally to specific numbers. However, it is unknown how the ratio of two numbers is represented, whether by processing numerator and denominator in separation, or by extending the analog magnitude code to relative quantity. Using functional MRI adaptation, we now show that populations of neurons in human fronto-parietal cortex are tuned to preferred fractions, generalizing across the format of presentation. After blood oxygen level-dependent signal adaptation to constant fractions, signal recovery to deviant fractions was modulated parametrically as a function of numerical distance between the deviant and adaptation fraction. The distance effect was invariant to changes in notation from number to word fractions and strongest in the anterior intraparietal sulcus, a key region for the processing of whole numbers. These findings demonstrate that the human brain uses the same analog magnitude code to represent both absolute and relative quantity. Our results have implications for mathematical education, which may be tailored to better harness our ability to access automatically a composite quantitative measure.