Biology subjects

Vatansever, D.

Publications and source records attributed to Vatansever, D..

13 recordsLinked to original sources

bioRxiv2026

CA1 reinstatement and novelty response independently support recognition memory

One of the central tensions in memory research is whether consistency or differentiation across events is beneficial for remembering. While theoretical models posit that the hippocampal subfield CA1 subserves both types of computations, it remains unclear how it can simultaneously express both in service of recognition memory. Here, we contrasted the two prominent functions of CA1: reinstatement (consistency) and novelty processing (differentiation) to address this gap. To this end, we analysed the Natural Scenes Dataset featuring eight participants who completed a continuous recognition memory task spanning 41 separate days with 213,000 trials in total. We calculated reinstatement and novelty indices for each image and then examined the degree to which these reflected successful memory encoding. We found that CA1 showed evidence for encoding-related reinstatement as well as for novelty processing even after controlling for each other. Reinstatement was specific to retrieving the initial representation during the first retrieval attempt and did not extend to other forms of reinstatement. Exploratory analyses additionally identified reinstatement in CA3, which exhibited different response profiles compared to CA1. Our work thus highlights that computations of consistency as well as differentiation can be orthogonal signals contributing independently to memory success and can simultaneously co-exist within the same region of the hippocampus.

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bioRxiv2026

Hippocampal subfields support human novelty detection via distinct signals

Detecting novelty is fundamental to adaptive memory, yet the neural comparisons that allow new events to be distinguished from prior experience are not fully understood. Hippocampal novelty signals are often framed as associative comparator responses that register violations of learned relationships. However, recognition memory models also predict a broader form of comparison: a global, item-based mismatch between an incoming stimulus and aggregate memory traces. Whether such global matching is implemented within human hippocampal circuitry, and whether it contributes to memory decisions, remains unknown. Using ultra-high-field 7T fMRI during dense sampling of a continuous object recognition task (76,800 trials across five sessions), we estimated both univariate novelty responses and multivariate global mismatch signals across hippocampal subfields. CA1 carried the novelty response that most reliably predicted accurate novelty detection, whereas the subiculum expressed a global mismatch signal that predicted detection independently of CA1. This subicular signal also shaped subsequent recognition behaviour, in which low global mismatch was associated with false alarms to novel objects that propagated into later hits. Finally, subicular global mismatch scaled with the experienced similarity of past events, consistent with an item-based comparison against accumulated memory. These findings identify distinct hippocampal mismatch signals for novelty detection and extend the human hippocampal comparator role beyond local associative mismatch to include global, item-based matching.

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bioRxiv2026

Two dominant axes structure high-dimensional object representations in the human ventral temporal cortex

The ventral temporal cortex is critical for visual object recognition, yet the principles organising its representations remain unclear. Using ultra-high-field 7T fMRI and dense sampling of 1,854 object concepts, we applied exploratory factor analysis to multivoxel response patterns to estimate the main axes of representational variation. Despite high dimensionality, over half of the explainable variance concentrated along two dominant axes: a continuum spanning objects of high biological salience, and a second integrating spatial context, physical scale, and manipulability. Importantly, neither reduced to a single semantic label, instead reflecting mixtures of visual and conceptual properties. Together they defined a triangular geometry, anchored by animal-, furniture- and food-related objects, stable across participants and two independent datasets, that mapped onto a lateral-to-medial cortical gradient, with category-selective regions emerging as local peaks within a broader continuum. These findings reveal that high-dimensional object representations in the ventral temporal cortex are structured by a small number of interpretable axes.

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bioRxiv2024

Functional divergence between the two cerebral hemispheres contributes to human fluid intelligence

Hemispheric lateralization is linked to potential cognitive advantages. It is considered a driving force behind the generation of human intelligence. However, establishing quantitative links between the degree of lateralization and intelligence in humans remains elusive. In this study, we propose a framework that utilizes the functional aligned multidimensional representation space derived from hemispheric functional gradients to compute between-hemisphere distances within this space. Applying this framework to a large cohort (N=777 from the Human Connectome Project), we identified high functional divergence across the two hemispheres within the frontoparietal control network. We found that both global divergence between the cerebral hemispheres and regional divergence within the multiple demand network were positively associated with fluid composite score and partially mediated the influence of brain size on individual differences in fluid intelligence. Together, these findings illuminate the profound significance of brain lateralization as a fundamental organizational principle of the human brain, providing direct evidence that hemispheric lateralization supports human fluid intelligence.

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bioRxiv2022

The right inferior frontal gyrus as pivotal node and effective regulator of the basal ganglia-thalamocortical response inhibition circuit in humans

The involvement of specific basal ganglia-thalamocortical circuits in response inhibition has been extensively mapped in the last few decades. However, the pivotal brain nodes and directed casual regulation within this inhibitory circuit in humans remains controversial. Here, we capitalize on recent progress in robust and biologically plausible directed causal modelling (DCM-PEB) and a large fMRI response inhibition dataset (n=218) to determine key nodes, their causal regulation and modulation via biological variables (sex) and inhibitory performance in the inhibitory control circuit encompassing the right inferior frontal gyrus (rIFG), caudate nucleus (rCau), globus pallidum (rGP) and thalamus (rThal).The entire neural circuit exhibited high intrinsic connectivity and an increasing rIFG inflow and its causal regulation over the rCau and rThal during response inhibition. In addition, sex and behavioral performance influenced the architecture of the regulatory circuits such that women displayed increased rThal self-inhibition and decreased rThal to GP modulation, while better inhibitory performance was associated with stronger rThal to rIFG communication. Furthermore, control analyses did not reveal a similar key communication in a left lateralized model. Together these findings indicate a pivotal role of the rIFG as input and causal regulator of subcortical response inhibition nodes.

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bioRxiv2021

Brain Laterality Dynamics Support Human Cognition

Hemispheric lateralization constitutes a core architectural principle of human brain organization underlying cognition, often argued to represent a stable, trait-like feature. However, emerging evidence underlines the inherently dynamic nature of brain networks, in which time-resolved alterations in functional lateralization remain uncharted. Integrating dynamic network approaches with the concept of hemispheric laterality, we map the spatiotemporal architecture of whole-brain lateralization in a large sample of high-quality resting-state fMRI data (N=991, Human Connectome Project). We reveal distinct laterality dynamics across lower-order sensorimotor systems and higher-order associative networks. Specifically, we expose two aspects of the laterality dynamics: laterality fluctuations, defined as the standard deviation of laterality time series, and laterality reversal, referring to the number of zero-crossings in laterality time series. These two measures are associated with moderate and extreme changes in laterality over time, respectively. While laterality fluctuations depict positive association with language function and cognitive flexibility, laterality reversal shows a negative association with the same neurocognitive factors. These opposing interactions indicate a dynamic balance between intra- and inter-hemispheric communication, i.e., segregation and integration of information across hemispheres. Furthermore, in their time-resolved laterality index, the default-mode and language networks correlate negatively with visual/sensorimotor and attention networks, indicating flexible while parallel processing capabilities that are linked to better out-of-scanner cognitive performance. Finally, the laterality dynamics correlate with regional metabolism and structural connectivity and showed significant heritability. Our results provide insights into the adaptive nature of the lateralized brain and new perspectives for future studies of human cognition, genetics and brain disorders.

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bioRxiv2020

Segregating domain-general from emotional context-specific inhibitory control systems - ventral striatum and orbitofrontal cortex serve as emotion-cognition integration hubs

Inhibitory control hierarchically regulates cognitive and emotional systems in the service of adaptive goal-directed behavior across changing task demands and environments. While previous studies convergently determined the contribution of prefrontal-striatal systems to general inhibitory control, findings on the specific circuits that mediate the context-specific impact of inhibitory control remained inconclusive. Against this background we employed an evaluated emotional Go/No Go task with fMRI in a large cohort of subjects (N = 250) to segregate brain systems and circuits that mediate domain-general from emotion-specific inhibition control. Particularly during a positive emotional context, behavioral results showed a lower accuracy for No Go trials and a faster response time for Go trials. While the dorsal striatum and lateral frontal regions were involved in inhibitory control irrespective of emotional context, activity in the ventral striatum (VS) and medial orbitofrontal cortex (mOFC) varied as a function of emotional context. On the voxel-wise network level, limbic and striatal systems generally exhibited highest changes in global brain connectivity during inhibitory control, while global brain connectivity of the left mOFC was less suppressed during emotional contexts. Functional connectivity analyses moreover revealed that negative coupling between the VS with inferior frontal gyrus (IFG)/insula and mOFC varied as a function of emotional context. Together these findings indicated separable domain general systems as well emotional context-specific inhibitory brain systems which specifically encompass the VS and its connections with frontal regions.

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bioRxiv2020

Connectivity patterns of task-specific brain networks allow individual prediction of cognitive symptom dimension of schizophrenia and link to molecular architecture

BackgroundDespite the marked inter-individual variability in the clinical presentation of schizophrenia, it remains unclear the extent to which individual dimensions of psychopathology may be reflected in variability across the collective set of functional brain connections. Here, we address this question using network-based predictive modeling of individual psychopathology along four data-driven symptom dimensions. Follow-up analyses assess the molecular underpinnings of predictive networks by relating them to neurotransmitter-receptor distribution patterns. MethodsWe investigated resting-state fMRI data from 147 schizophrenia patients recruited at seven sites. Individual expression along negative, positive, affective, and cognitive symptom dimensions was predicted using relevance vector machine based on functional connectivity within 17 meta-analytic task-networks following a repeated 10-fold cross-validation and leave-one-site-out analyses. Results were validated in an independent sample. Networks robustly predicting individual symptom dimensions were spatially correlated with density maps of nine receptors/transporters from prior molecular imaging in healthy populations. ResultsTen-fold and leave-one-site-out analyses revealed five predictive network-symptom associations. Connectivity within theory-of-mind, cognitive reappraisal, and mirror neuron networks predicted negative, positive, and affective symptom dimensions, respectively. Cognitive dimension was predicted by theory-of-mind and socio-affective-default networks. Importantly, these predictions generalized to the independent sample. Intriguingly, these two networks were positively associated with D1 dopamine receptor and serotonin reuptake transporter densities as well as dopamine-synthesis-capacity. ConclusionsWe revealed a robust association between intrinsic functional connectivity within networks for socio-affective processes and the cognitive dimension of psychopathology. By investigating the molecular architecture, the present work links dopaminergic and serotonergic systems with the functional topography of brain networks underlying cognitive symptoms in schizophrenia.

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bioRxiv2019

Emergence of neural dynamics within a co-ordinate space of large-scale neural hierarchies

When unoccupied by an explicit external task, humans engage in a wide range of different types of self-generated thinking. These are often unrelated to the immediate environment and have unique psychological features. Although contemporary perspectives on ongoing thought recognise the heterogeneity of these self-generated states, we lack both a clear understanding of how to classify the specific states, and how they can be mapped empirically. In the current study, we capitalise on advances in machine learning that allow continuous neural data to be divided into a set of distinct temporally re-occurring patterns, or states. We applied this technique to a large set of resting state data in which we also acquired retrospective descriptions of the participants experiences during the scan. We found that two of the identified states were predictive of patterns of thinking at rest. One state highlighted a pattern of neural activity commonly seen during demanding tasks, and the time individuals spent in this state was associated with descriptions of experience focused on problem solving in the future. A second state was associated with patterns of activity that are commonly seen under less demanding conditions, and the time spent in it was linked to reports of negative rumination. Finally, we found that these two neural states tended to fall at either end of a neural hierarchy that is thought to reflect the brains response to cognitive demands. Together, these results demonstrate that approaches which take advantage of time-varying changes in neural function can play an important role in understanding the repertoire of self-generated states. Moreover, they establish that important features of self-generated ongoing experience are related to variation along a similar vein to those seen when the brain responds to cognitive task demands.

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bioRxiv2019

Distinct patterns of thought mediate the link between brain functional connectome and psychological well-being

Ongoing thought patterns constitute important aspects of both healthy and abnormal human cognition. However, the neural mechanisms behind these daily experiences and their contribution to well-being remain a matter of debate. Here, using resting state fMRI and retrospective thought sampling in a large neurotypical cohort (n = 211) we identified two distinct patterns of thought, broadly describing the participants current concerns and future plans, that significantly explained variability in the individual functional connectomes. Consistent with the view that ongoing thoughts are an emergent property of multiple neural systems, network-based analysis highlighted the central importance of both unimodal and transmodal cortices in the generation of these experiences. Importantly, while state-dependent current concerns predicted better psychological health, mediating the effect of functional connectomes; trait-level future plans were related to better social health, yet with no mediatory influence. Collectively, we show that ongoing thoughts can influence the link between brain physiology and well-being.

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bioRxiv2019

Salient images: Evidence for a component process architecture for visual imagination.

The ability to visualise different people and places in imagination is a core element of human cognition. Contemporary neuroimaging research highlights regions of primary visual cortex as important in instantiating images in the minds eye. Here we combine task-based functional magnetic resonance imaging with measures of intrinsic brain organisation to show the ventral attention, or salience, network, also plays an important role in visual imagination. In a task-based study we replicated prior observations of regions of medial occipital cortex, including Brodmann Area 17, showing greater neural activity during imagination than when perceiving similar stimuli. In addition, we found regions of the ventral attention network, and in particular right dorsolateral prefrontal cortex (BA 9/46), were activated by the same acts of imagination. In a subsequent resting-state study, we demonstrated medial occipital cortex regions form a functional network with regions of the ventral attention network that were also active during imagination. Furthermore, this pattern was maximised in an overlapping region of right dorsolateral prefrontal cortex for individuals whose self-reported imagery had stronger negative affect. Together these data suggest visual imagination relies on functional interactions between regions of primary visual cortex with the ventral attention system, and in particular, with a region of right dorsolateral prefrontal cortex.

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bioRxiv2019

Hello, is that me you are looking for? A re-examination of the role of the DMN in off-task thought

Neural activity within the default mode network (DMN) is widely assumed to relate to processing during off-task states, however it remains unclear whether this association emerges from a shared role in self or social cognition. In the current study, we examine the possibility that the role of the DMN in ongoing thought emerges from contributions to specific features of off-task experience such as self-relevant or social content. A group of participants described their experiences while performing a laboratory task over a period of days. In a different session, neural activity was measured while participants performed self/other judgements. Despite the prominence of social and personal content in off-task reports, there was no association with neural activity during off-task trait adjective judgements. Instead, during both self and other judgements we found recruitment of caudal posterior cingulate cortex - a core DMN hub - was above baseline for individuals whose laboratory experiences were characterised as detailed. These data provide little support for a role of the DMN in self or other content in the off-task state and instead suggest a role in how on-going thought is represented.

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bioRxiv2018

Neural dynamics at rest associated with patterns of ongoing thought

Conscious experience is dynamic, and its fluidity is particularly marked when attention is not occupied by events in the external world and our minds are free to wander. Our study used measures of neural function, and advanced analyses techniques to examine how unconstrained neural state transitions relate to patterns of ongoing experience. Neural activity was recorded during wakeful rest using functional magnetic resonance imaging and Hidden Markov modelling identified recurrent patterns of brain activity constituting functional dynamic brain states. Individuals making more frequent transitions between states subsequently described experiences highlighting problem solving and lacking unpleasant intrusive features. Frequent switching between states also predicted better health and well-being as assessed by questionnaire. These data provide evidence that the fluidity with which individuals shift through dynamic neural states has an impact on the nature of ongoing thought, and suggest that greater flexibility at rest is an important indicator of a healthy mind.

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