Biology subjects

Khalighinejad, N.

Publications and source records attributed to Khalighinejad, N..

11 recordsLinked to original sources

bioRxiv2026

Ultrasound-mediated focal serotonin delivery causally modulates motivation in primates

Causal manipulation of neuromodulatory systems has been constrained by a trade-off between spatial precision and translational relevance: circuit-specific techniques are invasive, whereas systemic pharmacology lacks anatomical specificity. Here, we establish ultrasound-mediated neuromodulator delivery as a non-invasive, spatially precise approach for causal neuropharmacology in awake, behaving primates. By transiently opening the blood-brain barrier, we delivered systemically administered serotonin to the perigenual anterior cingulate cortex (pgACC) during a decision-making task. Combining computational modelling with multimodal imaging, pupillometry and histology, we show that elevating pgACC serotonin altered local neural activity and weakened the influence of reward environment on motivational state while leaving sensitivity to immediate reward opportunities intact. This was accompanied by reduced functional coupling, decreased local glutamatergic metabolite signal and increased serotonergic signal at the target, with repeated delivery well tolerated. Together, these findings establish a translatable platform for focal neuropharmacology and identify pgACC serotonin as a regulator of context-dependent motivation.

neuroscience↗

bioRxiv2025

Neurodynamics of prefrontal areas in volitional contexts: a comparative study based on computational modelling and EEG/ERP data

Volitional action arises from the interaction between internal intentions and external stimuli, yet the neural dynamics distinguishing self-initiated from externally triggered actions remain unclear. Here, we combine human EEG/ERP data with simulations from a phenomenological neurocomputational model of prefrontal control to examine the neurodynamic principles underlying different types of volitional behaviors. Using an extended version of our previously developed model, we generated neural activity patterns corresponding to self-initiated and externally triggered actions by manipulating the balance between endogenous and exogenous inputs to lateral prefrontal subregions. We then qualitatively compared these simulated dynamics with empirical EEG data from a perceptual decision-making task involving voluntary and instructed skip actions. Across both datasets, self-initiated actions showed a gradual buildup of activity, marked reductions in cross-trial variability, sharper state transitions, and beta-gamma frequency shifts; in contrast, externally triggered actions exhibited minimal variability reduction, weaker transitions, and largely stable frequency content. These convergent results suggest that self-initiated actions are supported by distinct preparatory dynamics, characterized by internal competition and stabilization of neural states, whereas externally triggered actions rely primarily on externally driven input. Together, these findings identify candidate neurodynamic signatures of intention formation and highlight how simplified computational models can reproduce and help explain key features of volitional control observed in human electrophysiology.

neuroscience↗

bioRxiv2025

Interpretable abstractions of artificial neural networks predict behavior and neural activity during human information gathering

It has been suggested that humans and other animals are driven by a fundamental desire to acquire information about opportunities available in their environments. Not only might such a desire explain pathological behaviors, but it may be needed to account for how everyday decisions are resolved. Here, we combine artificial neural networks (ANNs) with symbolic regression to extract an expressive yet interpretable model that specifies how human participants evaluate decision-relevant information during choice. This model accounts for behavior in our own data and in previous work, outperforming existing accounts of information sampling such as the Upper Confidence Bound heuristic. This modelling approach has broad potential for uncovering novel patterns in behavior and cognitive processes, while also specifying them in human-interpretable formats. We then used the value of information derived by our model, together with ultra-high field neuroimaging, to examine activity across a suite of subcortical neuromodulatory nuclei and two cortical regions that influence these nuclei. This established roles for midbrain dopaminergic nuclei, anterior cingulate cortex, and anterior insula in mediating the influence of value of information on behavior.

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bioRxiv2025

ACTIVITY IN HUMAN DORSAL RAPHE NUCLEUS SIGNALS CHANGES IN BEHAVIOURAL POLICY

The dorsal raphe nucleus (DRN) is an important source of serotonin to the human forebrain, however there is little consensus about its behavioural function. We build on recent results from animal models to demonstrate that activity in human DRN represents changes between general behavioural policies. We use a novel behavioural task to show that human participants change their policy to pursue or reject reward opportunities as a function of the average value of opportunities in the environment. Activity in DRN - but no other neuromodulatory nucleus - signalled such policy changes. Patterns of multivariate activity in dorsal anterior cingulate cortex (dACC) and anterior insular cortex (AI), meanwhile, tracked the relative value of reward opportunities given the average value of the environment. We therefore suggest that DRN, dACC and AI form a circuit in which dACC/AI compute the relative value of reward opportunities given the current context, and DRN implements changes in behavioural policy based on context-specific values.

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bioRxiv2024

DORSAL RAPHE NUCLEUS CONTROLS MOTIVATIONAL STATE TRANSITIONS IN MONKEYS

The dorsal raphe nucleus (DRN) is an important source of serotonin in the brain but fundamental aspects of its function remain elusive. Here, we present a combination of minimally invasive recording and disruption studies to show that DRN brings about changes in motivation states. We use recently developed methods for identifying temporal patterns in behaviour to show that monkeys change their motivation depending on the availability of rewards in the environment. Distinctive patterns of DRN activity occur when monkeys transition between a high motivation state occupied when rewards are abundant, to a low motivation state engendered by reward scarcity. Disrupting DRN diminishes sensitivity to the reward environment and perturbs transitions in motivational states.

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bioRxiv2024

General mechanisms of task engagement in the primate frontal cortex

Staying engaged with a task is necessary to maintain goal-directed behaviors. Although engagement varies with the specific task at hand it also exhibits continuous, intrinsic fluctuations widely. This intrinsic component of engagement is difficult to isolate behaviorally or neurally in controlled experiments with humans. By contrast, animals spontaneously move between periods of complete task engagement and disengagement, even in experimental settings. We, therefore, looked at behavior in macaques in a series of four tasks while recording fMRI signals. We identified consistent autocorrelation in task disengagement. This made it possible to build models capturing task-independent engagement and to link it to neural activity. Across all tasks, we identified common patterns of neural activity linked to impending task disengagement in mid-cingulate gyrus. By contrast, activity centered in perigenual anterior cingulate cortex (pgACC) was associated with maintenance of task performance. Importantly, we were able to carefully control for task-specific factors such as the reward history, choice value, and other motivational effects, such as response vigor, as indexed by response time, when identifying neural activity associated with task engagement. Moreover, we showed pgACC activity had a causal link to task engagement; in one of our tasks, transcranial ultrasound stimulation of pgACC, but not of control regions, changed task engagement/disengagement patterns.

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bioRxiv2023

An ancient subcortical circuit decides when to orient to threat in humans

Many psychiatric symptoms have been linked to threat-related perception and learning processes. In addition, however, there may also be mechanisms for balancing effectively between threat- and reward-related behaviors and these may also vary between individuals. We investigated neural activity associated with spontaneous switching between foraging for rewards and vigilance for threats with 7T fMRI. In a virtual naturalistic environment, participants freely switched between the two modes of behavior. Switching was driven by estimates of likelihood of threat and reward. Both tracking of threat and switching to vigilance were associated with specific but distributed patterns of activity spanning habenula, dorsal raphe nucleus (DRN), anterior cingulate cortex, and anterior insula cortex. Distinct distributed patterns heralded returns to reward-oriented behavior. Individual variation in DRN activity reflected individual variation in vigilance. All activity patterns were replicated in an initially held-out portion of data.

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bioRxiv2023

Dynamic off-resonance correction improves functional image analysis in fMRI of awake behaving non-human primates

Use of functional MRI in awake non-human primate (NHPs) has recently increased. Scanning animals while awake makes data collection possible in the absence of anaesthetic modulation and with an extended range of possible experimental designs. Robust awake NHP imaging however is challenging due to the strong artifacts caused by time-varying off-resonance changes introduced by the animals body motion. Recently, an image reconstruction technique has been proposed to estimate these off-resonance changes using the navigator data that is typically collected during fMRI scans to correct the data and compensate for the changes. In this study, we sought to thoroughly investigate the effect of this correction on the brain activation estimates using extended awake NHP data. Our results show significant improvements in image fidelity using our proposed correction strategy, as well as greatly enhanced and more reliable activation estimates in GLM analyses.

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bioRxiv2020

Differential functional connectivity underlying asymmetric reward-related activity in human and non-human primates

The orbitofrontal cortex (OFC) is a key brain region involved in complex cognitive functions such as reward processing and decision-making. Neuroimaging studies have shown unilateral OFC response to reward-related variables, however, those studies rarely discussed the lateralization of this effect. Yet, some lesion studies suggest that the left and right OFC contribute differently to cognitive processes. We hypothesized that the OFC asymmetrical response to reward could reflect underlying hemispherical difference in OFC functional connectivity. Using restingstate and reward-related MRI data from humans and from rhesus macaques, we first identified a specific asymmetrical response of the lateral OFC to reward in both species. Crucially, the subregion showing the highest reward-related asymmetry (RRA) overlapped with the region showing the highest functional connectivity asymmetry (FCA). Furthermore, the two types of functional asymmetries were found to be significantly correlated across humans. Altogether, our results suggest a similar pattern of functional specialization between the left and right OFC is present in two primate species.

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bioRxiv2018

Dissociating cognitive and motoric precursors of human self-initiated action

Across-trial variability of EEG decreases more markedly prior to self-initiated than prior to externally-triggered actions, providing a novel neural precursor for volitional action. However, it remains unclear whether this neural convergence is an early, deliberative stage, or a late, execution-related stage in the chain of cognitive processes that transform intentions to actions. We report two experiments addressing these questions. Self-initiated actions were operationalized as endogenous skip responses while waiting for target stimuli in a perceptual decision task. These self-initiated skips were compared to blocks where participants were instructed to skip. EEG variability decreased more markedly prior to self-initiated compared to externally-triggered skip actions, replicating previous findings.\n\nImportantly, this EEG convergence was stronger at fronto-midline electrodes than at either the electrode contralateral or ipsilateral to the hand assigned to the skip action in each block (Experiment 1). Further, convergence was stronger when availability of skip responses was rationed, encouraging deliberate planning before skipping (Experiment 2). This suggests that the initiation of voluntary actions involves a bilaterally-distributed, effector-independent process related to deliberation. A consistent process of volition is detectable during early, deliberative planning, and not only during late, execution-related time windows.

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bioRxiv2017

Human Self-Initiated Action Is Preceded By A Reliable Process Of Noise Reduction

A gradual buildup of electrical potential over motor areas precedes self-initiated movements. Recently, such \"readiness potentials\" (RPs) were attributed to stochastic fluctuations in neural activity. We developed a new experimental paradigm that operationalised self-initiated actions as endogenous skip responses while waiting for target stimuli in a perceptual decision task. We compared these to a block of trials where participants could not choose when to skip, but were instead instructed to skip. Frequency and timing of motor action were therefore balanced across blocks, so that conditions differed only in how the timing of skip decisions was generated. We reasoned that across-trial variability of EEG could carry as much information about the source of skip decisions as the mean RP. EEG variability decreased more markedly prior to self-initiated compared to externally-triggered skip actions. This convergence suggests a consistent preparatory process prior to self-initiated action. A leaky stochastic accumulator model could reproduce this convergence given the additional assumption of a systematic decrease in input noise prior to self-initiated actions. Our results may provide a novel neurophysiological perspective on the topical debate regarding whether self-initiated actions arise from a deterministic neurocognitive process, or from neural stochasticity. We suggest that the key precursor of self-initiated action may manifest as a reduction in neural noise.

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