Biology subjects

Gotts, S. J.

Publications and source records attributed to Gotts, S. J..

14 recordsLinked to original sources

bioRxiv2025

Repetition-related reductions in neural activity support improved behavior through increases in oscillatory power

Repeatedly processing an object leads to subsequent behavioral improvements in its identification and reductions in associated neural activity, a form of neural processing efficiency that multiple theoretical models have attempted to explain. Using simultaneous fMRI-EEG in humans during object naming, we find that stimulus-driven oscillatory power from high (gamma) to low frequencies (theta) increases and resolves earlier with repetition in task-engaged frontal and occipitotemporal brain regions identified as showing repetition suppression in fMRI. Changes in gamma oscillatory power in these regions were correlated with behavioral priming across subjects and additionally with fMRI repetition suppression in left frontal cortex, providing multimodal support for a novel mixture of the previously proposed Synchrony and Facilitation models.

neuroscience↗

bioRxiv2023

A functional parcellation of the whole brain in individuals with autism spectrum disorder reveals atypical patterns of network organization

BACKGROUNDResearchers studying autism spectrum disorder (ASD) lack a comprehensive map of the functional network topography in the ASD brain. We used high-quality resting state functional MRI (rs-fMRI) connectivity data and a robust parcellation routine to provide a whole-brain map of functional networks in a group of seventy individuals with ASD and a group of seventy typically developing (TD) individuals. METHODSThe rs-fMRI data were collected using an imaging sequence optimized to achieve high temporal signal-to-noise ratio (tSNR) across the whole-brain. We identified functional networks using a parcellation routine that intrinsically incorporates stability and replicability of the networks by keeping only network distinctions that agree across halves of the data over multiple random iterations in each group. The groups were tightly matched on tSNR, in-scanner motion, age, and IQ. RESULTSWe compared the maps from each group and found that functional networks in the ASD group are atypical in three seemingly related ways: 1) whole-brain connectivity patterns are less stable across voxels within multiple functional networks, 2) the cerebellum, subcortex, and hippocampus show weaker differentiation of functional subnetworks, and 3) subcortical structures and the hippocampus are atypically integrated with the neocortex. CONCLUSIONSThese results were statistically robust and suggest that patterns of network connectivity between the neocortex and the cerebellum, subcortical structures, and hippocampus are atypical in ASD individuals.

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bioRxiv2022

Compensation and conversation in autism: atypical connectivity supports typical behavior

BackgroundIt is well-established that individuals with autism show atypical functional brain connectivity. However, the role this plays in behavior, especially in naturalistic social settings, has remained unclear. Some atypical patterns may reflect core deficits, while others may instead compensate for deficits and promote adaptive behavior. Distinguishing these possibilities requires measuring the typicality of spontaneous behavior and determining which connectivity patterns correlate with it. MethodsThirty-nine male participants (19 autism, 20 typically-developed) engaged in 115 spontaneous conversations with an experimenter during fMRI scanning (Jasmin, et al., 2019, Brain). A classifier algorithm was trained to distinguish participants by diagnosis based on 81 semantic, affective and linguistic dimensions derived from their use of language. The algorithms certainty that a participant was in either the autism or typical group was used as a measure of task performance and compared with functional connectivity levels. ResultsThe algorithm accurately classified participants (74%, P = .002), and its scores correlated with clinician-observed autism signs (ADOS) (rs = .56, P = .03). In support of a compensatory role, greater functional connectivity, most prominently between left-hemisphere social communication regions and right inferior frontal cortex, correlated with more typical language behaviour, only for the autism group (rs = .56, P = .01). ConclusionWe report a simple and highly generalizable method for quantifying behavioral performance and neural compensation during complex spontaneous social behavior, without the need for an a priori benchmark. The findings suggest that functional connectivity increases in autism during communication reflect a neural compensation strategy.

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bioRxiv2021

A comparison of single and multi-echo processing of fMRI data during overt autobiographical recall

Recent years have seen an increase in the use of multi-echo fMRI designs by cognitive neuroscientists. Acquiring multiple echoes allows one to reduce thermal noise and identify nuisance signal components in BOLD data (Kundu et al., 2012). At the same time, multi-echo acquisitions increase data processing complexity and may incur a cost to the temporal and spatial resolution of the acquired data. Here, we re-examine a multi-echo dataset (Gilmore et al., 2021a) analyzed using multi-echo ICA (ME-ICA) and focused on hippocampal activity during the overly spoken recall of recent and remote autobiographical memories. The goal of the present series of analyses was to determine if ME-ICAs theoretical denoising benefits might lead to a practical difference in the overall conclusions reached. Compared to single echo data, ME-ICA led to qualitatively different conclusions regarding hippocampal contributions to autobiographical recall: whereas the single echo analysis largely failed to reveal hippocampal activity relative to an active baseline, ME-ICA results supported predictions of the Standard Model of Consolidation and a time limited hippocampal involvement (Alvarez and Squire, 1994). These data provide a practical example of the benefits multi-echo denoising in a naturalistic memory paradigm and demonstrate how they can be used to address long-standing theoretical questions.

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bioRxiv2020

Resting-state functional connectivity and psychopathology in Klinefelter syndrome (47, XXY)

Klinefelter syndrome (47, XXY; Henceforth: XXY syndrome) is a high impact but poorly understood genetic risk factor for neuropsychiatric impairment. Here, we provide the first neuroimaging study to map resting-state functional connectivity (rsFC) changes in XXY syndrome and ask how these might relate to brain anatomy and psychopathology. We collected resting state functional magnetic resonance imaging data from 75 individuals with XXY and 84 healthy XY males. We implemented a brain-wide screen to identify regions with altered global rsFC in XXY vs. XY males, and then used seed-based analysis to decompose these alterations. We further compared rsFC changes with regional changes in brain volume from voxel-based morphometry and tested for correlations between rsFC and symptom variation within XXY syndrome. We found that XXY syndrome was characterized by increased global rsFC in the left dorsolateral prefrontal cortex (DLPFC), associated with overconnectivity with diverse rsFC networks. Regional rsFC changes were partly coupled to regional volumetric changes in XXY syndrome. Within the precuneus, variation in DLPFC rsFC within XXY syndrome was correlated with the severity of psychopathology in XXY individuals. Our findings provide the first view of altered functional brain connectivity in XXY syndrome and delineate links between these alterations and those relating to both brain anatomy and psychopathology. Taken together, these insights advance biological understanding of XXY syndrome as a disorder in its own right, and as a model of genetic risk for psychopathology more broadly.

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bioRxiv2020

The human hippocampus plays a time-limited role in retrieving autobiographical memories

The necessity of the human hippocampus for remote autobiographical recall remains fiercely debated. The standard model of consolidation predicts a time-limited role for the hippocampus, but the competing multiple trace/trace transformation theories posit indefinite involvement. Lesion evidence remains inconclusive, and the inferences one can draw from fMRI have been limited by reliance on covert (silent) recall, which obscures dynamic, moment-to-moment content of retrieved memories. Here, we capitalized on advances in fMRI denoising to employ overtly spoken recall. Forty participants retrieved recent and remote memories, describing each for approximately two minutes. Details associated with each memory were identified and modeled in the fMRI timeseries data using a variant of the Autobiographical Interview procedure, and activity associated with the recall of recent and remote memories was then compared. Posterior hippocampal regions exhibited temporally-graded activity patterns (recent events > remote events), as did several regions of frontal and parietal cortex. Consistent with predictions of the standard model, recall-related hippocampal activity differed from a non-autobiographical control task only for recent, and not remote, events. Task-based connectivity between posterior hippocampal regions and others associated with mental scene construction also exhibited a temporal gradient, with greater connectivity accompanying the recall of recent events. These findings support predictions of the standard model of consolidation and demonstrate the potential benefits of overt recall in neuroimaging experiments.

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bioRxiv2020

Tasting Pictures: Viewing Images of Foods Evokes Taste-Quality-Specific Activity in Gustatory Insular Cortex

Previous studies have shown that the conceptual representation of food involves brain regions associated with taste perception. The specificity of this response, however, is unknown. Does viewing pictures of food produce a general, non-specific response in taste-sensitive regions of the brain? Or, is the response specific for how a particular food tastes? Building on recent findings that specific tastes can be decoded from taste-sensitive regions of insular cortex, we asked whether viewing pictures of foods associated with a specific taste (e.g., sweet, salty, sour) can also be decoded from these same regions and if so, are the patterns of neural activity elicited by the pictures and their associated tastes similar? Using ultra-high resolution functional magnetic resonance imaging at high magnetic field strength (7-Tesla), we were able to decode specific tastes delivered during scanning, as well as the specific taste category associated with food pictures within the dorsal mid-insula, a primary taste responsive region of brain. Thus, merely viewing food pictures triggers an automatic retrieval of specific taste quality information associated with the depicted foods, within gustatory cortex. However, the patterns of activity elicited by pictures and their associated tastes were unrelated, thus suggesting a clear neural distinction between inferred and directly experienced sensory events. These data show how higher-order inferences derived from stimuli in one modality (i.e. vision) can be represented in brain regions typically thought to represent only low-level information about a different modality (i.e. taste). Significance StatementDoes a picture of an apple taste sweet? Previous studies have shown that viewing food pictures activates brain regions involved in taste perception. However, its unclear if this response is actually specific to the taste of depicted foods. Using ultra-high resolution functional magnetic resonance imaging and multi-voxel pattern analysis, we decoded specific tastes delivered during scanning, as well as the dominant tastes associated with food pictures within primary taste cortex. Thus, merely viewing pictures of food evokes an automatic retrieval of information about the taste of those foods. These results show how higher-order information from one sensory modality (i.e. vision) can be represented in brain regions thought to represent only low-level information from a different modality (i.e. taste).

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bioRxiv2020

Callosal anisotropy predicts attentional network changes after parietal inhibitory stimulation

Hemispatial neglect is thought to result from disruption of interhemispheric equilibrium. Right hemisphere lesions deactivate the right frontoparietal network and hyperactivate the left via release from interhemispheric inhibition. Support for this theory comes from neuropsychological evidence as well as transcranial magnetic stimulation (TMS) studies in healthy subjects, in whom right posterior parietal cortex (PPC) inhibition causes neglect-like, rightward, visuospatial bias. Concurrent TMS and fMRI after right PPC TMS show task-dependent changes but may fail to identify effects of stimulation in areas not directly activated by the specific task, complicating interpretations. We used resting-state functional connectivity (RSFC) after inhibitory TMS over the right PPC to examine changes in the networks underlying visuospatial attention. In a crossover experiment in healthy individuals, we delivered continuous theta burst TMS to the right PPC and vertex as control condition. We hypothesized that PPC inhibitory stimulation would cause a rightward visuospatial bias, decrease PPC connectivity with frontal areas, and increase PPC connectivity with the attentional network in the left hemisphere. We also expected that individual differences in fractional anisotropy (FA) in white matter connections between the PPCs would account for variability in TMS-induced RSFC changes. As expected, TMS over the right PPC caused a rightward shift in line bisection judgment and increased RSFC between the right PPC and the left superior temporal gyrus. This effect was inversely related to FA in the posterior corpus callosum. Local inhibition of the right PPC reshapes connectivity in the attentional network and depends on interhemispheric connections.

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bioRxiv2020

Enhanced inter-regional coupling of neural responses underlies long-term behavioral priming

Stimulus identification commonly improves with repetition over long delays ("repetition priming"), whereas neural activity commonly decreases ("repetition suppression"). Multiple models have been proposed to explain this brain-behavior relationship, predicting alterations in functional and/or effective connectivity (Synchrony and Predictive Coding models), in the latency of neural responses (Facilitation model), and in the relative similarity of neural representations (Sharpening model). Here, we test these predictions with fMRI during overt and covert naming of repeated and novel objects. While we find partial support for predictions of the Facilitation and Sharpening models in the left fusiform gyrus and left frontal cortex, the strongest support was observed for the Synchrony model, with increased coupling between right temporoparietal and anterior cingulate cortex for repeated objects that correlated with priming magnitude across participants. Despite overlap with regions showing repetition suppression, increased coupling and repetition suppression varied independently, establishing that they follow from distinct mechanisms. HighlightsO_LITested four prominent neural models of repetition suppression and long-term priming C_LIO_LIConnectivity analyses supported Synchrony model but not Predictive Coding model C_LIO_LITiming, spatial similarity of responses partially support Facilitation, Sharpening C_LIO_LIRepetition suppression was independent of coupling, implying distinct mechanisms C_LI eTOCGotts et al. test four prominent neural models of repetition suppression and behavioral priming. They show that the model with the most support is the Synchrony model: a whole-brain connectivity analysis revealed that temporoparietal cortex has increased coupling with anterior cingulate cortex following repetition, particularly for strongly primed objects.

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bioRxiv2019

Taste quality representation in the human brain

In the mammalian brain, the insula is the primary cortical substrate involved in the perception of taste. Recent imaging studies in rodents have identified a gustotopic organization in the insula, whereby distinct insula regions are selectively responsive to one of the five basic tastes. However, numerous studies in monkeys have reported that gustatory cortical neurons are broadly-tuned to multiple tastes, and tastes are not represented in discrete spatial locations. Neuroimaging studies in humans have thus far been unable to discern between these two models, though this may be due to the relatively low spatial resolution employed in taste studies to date. In the present study, we examined the spatial representation of taste within the human brain using ultra-high resolution functional magnetic resonance imaging (MRI) at high magnetic field strength (7-Tesla). During scanning, participants tasted sweet, salty, sour and tasteless liquids, delivered via a custom-built MRI-compatible tastant-delivery system. Our univariate analyses revealed that all tastes (vs. tasteless) activated primary taste cortex within the bilateral dorsal mid-insula, but no brain region exhibited a consistent preference for any individual taste. However, our multivariate searchlight analyses were able to reliably decode the identity of distinct tastes within those mid-insula regions, as well as brain regions involved in affect and reward, such as the striatum, orbitofrontal cortex, and amygdala. These results suggest that taste quality is not represented topographically, but by a combinatorial spatial code, both within primary taste cortex as well as regions involved in processing the hedonic and aversive properties of taste.

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bioRxiv2019

Brain regions with positive and negative task-evoked responses engage in cooperative rather than competitive interactions

Brain regions displaying task-induced decreases in activity, sometimes referred to as \"Task-Negative\", have been proposed to reflect cortico-cortical competition from regions showing task-induced increases in activity, sometimes referred to as \"Task-Positive\". If these functional networks are competitive, trial-level fMRI BOLD responses across voxels exhibiting Positive and Negative responses should be anti-correlated. Additionally, the correlation between the BOLD response and behavior in Positive and Negative regions should have opposite sign. Here, we test these predictions using trial-to-trial variability in an object naming task. In contrast to the negative coupling proposed by a competition model, we find positive coupling between Positive and Negative regions and show that this coupling aligns with trial-level behavioral correlations. We provide evidence that these cooperative interactions are not due to a non-specific global factor and discuss alternative proposals, such as thalamo-cortical gating.\n\nHighlightsO_LITested competitive interactions among positive and negative task-evoked regions\nC_LIO_LIPositive and negative regions exhibited positive coupling at trial and run levels\nC_LIO_LISmaller competitive effects seen in BOLD-behavior correlations\nC_LIO_LIStrong cooperative effects not due to a non-specific common global factor\nC_LI\n\neTOCCsumitta et al. show that positive and negative BOLD responses do not exhibit cortical competition among corresponding brain regions. Rather, these networks display positive coupling. The spatial distribution of positive coupling aligned with behavioral correlations, suggesting normal, cooperative network interactions.

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bioRxiv2019

Prism adaptation modulates connectivity of the intraparietal sulcus with multiple brain networks

Prism adaptation (PA) alters spatial cognition according to the direction of visual displacement by temporarily modifying sensorimotor mapping. Right-shifting prisms (right PA) improve neglect of left space in patients, possibly by decreasing activity in the left hemisphere and increasing it in the right. Left PA shifts attention to the right in healthy individuals by an opposite mechanism. However, functional imaging studies of PA are inconsistent, perhaps because of differing activation tasks. We measured resting-state functional connectivity (RSFC) in healthy individuals before and after PA. Right, vs. left, PA decreased RSFC in the navigation network defined by the right posterior parietal cortices (PPCs), hippocampus, and cerebellum. Right PA, relative to baseline, increased RSFC between regions within both PPCs and between the PPCs and the right middle frontal gyrus, whereas left PA decreased RSFC between these regions. These results show that right PA modulates connectivity within the right-hemisphere navigation network and shifts attention leftward by increasing connectivity in the right frontoparietal network and left PA produces essentially opposite effects, consistent with the interhemispheric competition model. These finding explain the action of PA on intact cognition and will help optimize interventions in neglect patients.

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bioRxiv2017

Brain networks, dimensionality, and global signal averaging in resting-state fMRI: Hierarchical network structure results in low-dimensional spatiotemporal dynamics

One of the most controversial practices in resting-state fMRI functional connectivity studies is whether or not to regress out the global average brain signal (GS) during artifact removal. Some groups have argued that it is absolutely essential to regress out the GS in order to fully remove head motion, respiration, and other global imaging artifacts. Others have argued that removing the GS distorts the resulting correlation matrices, qualitatively alters the results of group comparisons, and impairs relationships to behavior. At the core of this argument is the assessment of dimensionality in terms of the number of brain networks with uncorrelated time series. If the dimensionality is high, then the distortions due to GS removal could be effectively negligible. In the current paper, we examine the dimensionality of resting-state fMRI data using principal component analyses (PCA) and network clustering analyses. In two independent datasets (Set 1: N=62, Set 2: N=32), scree plots of the eigenvalues level off at or prior to 10 principal components, with prominent elbows at 3 and 7 components. While network clustering analyses have previously demonstrated that numerous networks can be distinguished with high thresholding of the voxel-wise correlation matrices, lower thresholding reveals a lower-dimensional hierarchical structure, with the first prominent branch at 2 networks (corresponding to the previously described \"task-positive\"/\"task-negative\" distinction) and further stable subdivisions at 4, 7 and 17. Since inter-correlated time series within these larger branches do not cancel to zero when averaged, the hierarchical nature of the correlation structure results in much lower effective dimensionality. Consistent with this, partial correlation analyses revealed that network-specific variance remains present in the GS at each level of the hierarchy, accounting for at least 18-20% of the overall GS variance in each dataset. These results demonstrate that GS regression is expected to remove substantial portions of neurogenic brain signals along with artifacts. We highlight alternative means of controlling for residual global artifacts when not removing the GS.

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bioRxiv2017

Direct Modulation Of Aberrant Brain Network Connectivity Through Real-Time NeuroFeedback

The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained 3 brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. 17 ASD participants and 10 control participants were scanned over multiple sessions (123 sessions in total). Desired network connectivity patterns were reinforced in real-time, without participants awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns.\n\nSignificance StatementMany disorders are characterized by underlying abnormalities in network connectivity. These abnormalities are difficult to address with explicit training procedures (which are unlikely to target the specific abnormalities). Covert neurofeedback however, can directly target these networks, positively reinforcing the desired connections. We have developed a method for reinforcing correlations in real-time, and show that such training is effective, inducing significant, long-lasting changes in connectivity between aberrant networks in Autism Spectrum Disorder. This provides a potential mechanism for modulating aberrant correlation structures in other clinical groups as well.

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