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Somers, D. C.

Publications and source records attributed to Somers, D. C..

6 recordsLinked to original sources

Gradients of function between sensory drive and working memory in human frontal cortex

The coordination of sensory processing and working memory (WM) is fundamental to cognition. Spatial organization of sensory processing and WM is known to be broadly distributed across the cortex, but finer-scale organization at the interfaces between these functions remains understudied. Although the notion of sharp parcellations of cortex into distinct functional modules dominates the field, a growing body of works support graded changes in function and anatomy in some cortical zones. Based on this and potential advantages of gradient organizational structure in frontal cortex, we hypothesized that sensory-WM interfaces in the frontal cortex are gradient-like, not boundary-like. We examined twenty bilateral cortical regions that participate in visual/auditory WM tasks. In five frontal cortical regions, group-level WM activation overlapped with sensory drive, but was spatially shifted. We compared subject-level (N=20) boundary and gradient models of change in function. Strong individual-level evidence for sensory-WM gradients was observed in pre-supplementary motor area, ventral premotor cortex, and anterior insula in both modalities and in dorsal premotor cortex for visual WM. Conversely, dorsolateral pre-frontal cortex yielded mixed results, favored distinct WM and sensory regions in the left hemisphere, and gave some evidence for gradients in the right hemisphere. These results provide evidence that sensory and WM regions in frontal cortex are largely not distinct with sharp boundaries at their interfaces but instead bleed into each other to form local rostral-caudal sensory-WM gradients. We speculate these gradients may allow efficient interfacing between sensory and WM representations, and/or fine-grained, task-dependent shifting between bottom-up sensory and top-down influences.

neuroscience↗

Dynamic task-based reorganization of sensory-biased and supramodal working memory networks in the human cerebral cortex

Human working memory is supported by a broadly distributed set of brain networks. Content-specific networks communicate with a domain-general, supramodal network that is recruited regardless of the type of content. Here, we contrasted visual and auditory working memory tasks to examine interactions between the supramodal network and two content-specific networks. Functional connectivity among visual-biased, auditory-biased, and supramodal working memory networks was assayed by collecting task and resting-state fMRI data from 24 human participants (age 18-43; 11 men and 13 women). At rest, as found previously, the supramodal network exhibited stronger functional connectivity with the visual-biased network than with the auditory-biased network. This asymmetry raises questions about how networks communicate to support robust performance across modalities. However, during auditory task performance, dynamic changes increased auditory network connectivity with supramodal and visual-biased frontal regions, while decreasing connectivity from posterior visual areas to supramodal and frontal visual regions. In contrast, the visual task produced weak changes. Across individuals, auditory working memory precision correlated with the strength of auditory network connectivity changes, while no such brain-behavior link was observed for visual working memory. These results demonstrate an asymmetry in working memory network organization and reveal that dynamic reorganization accompanies performance of working memory tasks.

neuroscience↗

Combined Auditory, Tactile, and Visual fMRI Reveals Sensory-Biased and Supramodal Working Memory Regions in Human Frontal Cortex

Selectivity for sensory modality characterizes distinct subregions of the human brain, well beyond the primary sensory cortices. We previously identified frontal and posterior cortical regions that are preferentially recruited for visual vs. auditory attention and working memory (WM). Here, we extend our approach to include tactile cognition and to characterize cortical regions recruited by WM in each of three sensory modalities. The joint organization of visual-selective, auditory-selective, tactile-selective, and supramodal WM recruitment within individual subjects has not been fully investigated previously. Male and female human subjects participated in a blocked fMRI task requiring them to perform N-back WM judgements in auditory, visual, or tactile (haptic) modalities. We confirmed our prior reports of multiple visual-biased and auditory-biased frontal lobe regions. We also observed several bilateral tactile-selective regions abutting previously described visual- and auditory-selective regions, including dorsal and ventral precentral sulcus, the postcentral sulcus, and the anterior intraparietal sulcus. Several cortical regions were recruited by WM in all three sensory modalities in individual subjects, including precentral sulcus, inferior frontal sulcus, intraparietal sulcus, anterior insula and pre-supplementary motor area. Supramodal regions exhibited substantial overlap with visual-biased regions in frontal and parietal cortex and comparatively little overlap with tactile- or auditory-biased regions. Lastly, resting-state analyses revealed that auditory-, visual- and tactile-selective WM regions segregate into modality-specific networks that span frontal and posterior cortex. Together, these results shed light on the functional organization of sensory-selective and supramodal regions supporting higher-order cognition. SIGNIFICANCE STATEMENTUsing within-subject fMRI analyses of three different sensory modalities, we identify the fine-scale architecture of sensory-biased and supramodal working memory structures within human frontal cortex. Sixteen bilateral frontal lobe regions are identified: five auditory-biased, four visual-biased, two tactile-biased, and five multiple-demand / supramodal regions. These parcels are largely distinct with the notable exception that the visual-biased regions each partially overlap with supramodal regions, suggesting a tight link between visual and supramodal working memory representations. Sensory-biased frontal lobe regions form modality-specific networks with traditionally-identified posterior sensory cortical regions. The findings demonstrate a pervasive role for sensory modality in the functional organization of frontal cortex and offer a fine-scale parcellation of the human frontal lobe regions supporting working memory.

neuroscience↗

Predicting an Individual's Cerebellar Activity from Functional Connectivity Fingerprints

The cerebellum is gaining scientific attention as a key neural substrate of cognitive function; however, individual differences in the cerebellar organization have not yet been well studied. Individual differences in functional brain organization can be closely tied to individual differences in brain connectivity. Connectome Fingerprinting is a modeling approach that predicts an individuals brain activity from their connectome. Here, we extend Connectome Fingerprinting (CF) to the cerebellum. We examined functional MRI data from 160 subjects (98 females) of the Human Connectome Project young adult dataset. For each of seven cognitive task paradigms, we constructed CF models from task activation maps and resting-state cortico-cerebellar functional connectomes, using a set of training subjects. For each model, we then predicted task activation in novel individual subjects, using their resting-state functional connectomes. In each cognitive paradigm, the CF models predicted individual subject cerebellar activity patterns with significantly greater precision than did predictions from the group average task activation. Examination of the CF models revealed that the cortico-cerebellar connections that carried the most information were those made with the non-motor portions of the cerebral cortex. These results demonstrate that the fine-scale functional connectivity between the cerebral cortex and cerebellum carries important information about individual differences in cerebellar functional organization. Additionally, CF modeling may be useful in the examination of patients with cerebellar dysfunction, since model predictions require only resting-state fMRI data which is more easily obtained than task fMRI.

neuroscience↗

Default Mode and Dorsal Attention Network functional connectivity associated with alpha and beta peak frequency in individuals.

Alpha- and Beta-frequency oscillatory waves are evident in resting-state electro- and magneto-encephalography (EEG, MEG). Higher peak frequencies for Alpha and Beta are associated with greater cognitive health. Aging slows down the alpha and beta waves which are also affected by mental states, disorders such as ADHD, and sleep deprivation. Functional magnetic resonance imaging (fMRI) of resting-state brain activity reveals anti-correlation of very low frequency (< 0.1 Hz) fluctuations between two distributed cerebral cortical networks, the Dorsal Attention Network (DAN) and the Default Mode Network (DMN). DAN activation is related to attentional demands in extrinsic tasks, whereas DMN is associated with mind wandering, episodic memory retrieval, and intrinsic processing. Prior research has found that higher DAN-DMN anticorrelation is related to greater cognitive and mental health. Here, we investigated whether these two measures of cognitive and mental health are related to each other within individuals. We investigated resting-state Functional Connectivity (rsFC) between the DMN and DAN using fMRI and alpha and beta peaks from MEG using two large datasets (n=89 and n=189). We found that more robust anti-correlations between DMN and DAN regions are related to higher peak frequencies of alpha and beta rhythms in the brain. Subjects with higher alpha peak frequencies also show stronger positive within-network connectivity in both the DMN and DAN networks. Females show stronger correspondence between the two measures as compared to males. This association between two non-invasive cognitive neuroscience modalities adds to the growing literature on the biomarkers of cognitive and mental health. Key pointsO_LIMEG/EEG biomarker of brain health is correlated with rs-fMRI biomarker of brain health C_LIO_LIAlpha and beta peak frequency correlated with DMN-DAN functional connectivity C_LIO_LIStronger within-network connectivity for subjects with a high alpha peak frequency C_LIO_LIFemales have a stronger association between peak frequency and DMN-DAN connectivity C_LI

neuroscience↗

Extended frontal networks for visual and auditory working memory

Working memory (WM) supports the persistent representation of transient sensory information. Visual and auditory stimuli place different demands on WM and recruit different brain networks. Separate auditory- and visual-biased WM networks extend into the frontal lobes, but several challenges confront attempts to parcellate human frontal cortex, including fine-grained organization and between-subject variability. Here, we use differential intrinsic functional connectivity from two visual-biased and two auditory-biased frontal structures to identify additional candidate sensory-biased regions in frontal cortex. We then examine direct contrasts of task fMRI during visual vs. auditory 2-back WM to validate those candidate regions. Three visual-biased and five auditory-biased regions are robustly activated bilaterally in the frontal lobes of individual subjects (N=14, 7 women). These regions exhibit a sensory preference during passive exposure to task stimuli, and that preference is stronger during WM. Hierarchical clustering analysis of intrinsic connectivity among novel and previously identified bilateral sensory-biased regions confirms that they functionally segregate into visual and auditory networks, even though the networks are anatomically interdigitated. We also observe that the fronto-temporal auditory WM network is highly selective and exhibits strong functional connectivity to structures serving non-WM functions, while the fronto-parietal visual WM network hierarchically merges into the multiple-demand cognitive system.

neuroscience↗