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Shahdloo, M.

Publications and source records attributed to Shahdloo, M..

6 recordsLinked to original sources

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.

neuroscience↗

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.

neuroscience↗

Model-based dynamic off-resonance correction for improved accelerated fMRI in awake behaving non-human primates

PurposeTo estimate dynamic off-resonance due to vigorous body motion in accelerated fMRI of awake behaving non-human primates (NHPs) using the standard EPI 3-line navigator, in order to attenuate the effects of time-varying off-resonance on the reconstruction. MethodsIn NHP fMRI the animals head is usually head-posted, and the dynamic off-resonance is mainly caused by motion in body parts that are distant from the brain and have low spatial frequency. Hence, off-resonance at each frame can be approximated as a spatially linear perturbation of the off-resonance at a reference frame, and is manifested as a relative linear shift in k-space. Using GRAPPA operators, we estimated these shifts by comparing the 3-line navigator at each time frame with that at the reference frame. Estimated shifts were then used to correct the data at each frame. The proposed method was evaluated in phantom scans, simulations, and in vivo data. ResultsThe proposed method is shown to successfully estimate low-spatial order dynamic off-resonance perturbations, including induced linear off-resonance perturbations in phantoms, and is able to correct retrospectively corrupted data in simulations. Finally, it is shown to reduce ghosting artifacts and geometric distortions by up to 20% in simultaneous multi-slice in vivo acquisitions in awake-behaving NHPs. ConclusionA method is proposed that does not need any sequence modification or extra acquisitions and makes accelerated awake behaving NHP imaging more robust and reliable, reducing the gap between what is possible with NHP protocols and state-of-the-art human imaging.

neuroscience↗

Task-Dependent Warping of Semantic Representations During Search for Visual Action Categories

Object and action perception in cluttered dynamic natural scenes relies on efficient allocation of limited brain resources to prioritize the attended targets over distractors. It has been suggested that during visual search for objects, distributed semantic representation of hundreds of object categories is warped to expand the representation of targets. Yet, little is known about whether and where in the brain visual search for action categories modulates semantic representations. To address this fundamental question, we studied human brain activity recorded via functional magnetic resonance imaging while subjects viewed natural movies and searched for either communication or locomotion actions. We find that attention directed to action categories elicits tuning shifts that warp semantic representations broadly across neocortex, and that these shifts interact with intrinsic selectivity of cortical voxels for target actions. These results suggest that attention serves to facilitate task performance during social interactions by dynamically shifting semantic selectivity towards target actions, and that tuning shifts are a general feature of conceptual representations in the brain.

neuroscience↗

Attentional Modulation of Hierarchical Speech Representations in a Multi-Talker Environment

Humans are remarkably adept in listening to a desired speaker in a crowded environment, while filtering out non-target speakers in the background. Attention is key to solving this difficult cocktail-party task, yet a detailed characterization of attentional effects on speech representations is lacking. It remains unclear across what levels of speech features and how much attentional modulation occurs in each brain area during the cocktail-party task. To address these questions, we recorded whole-brain BOLD responses while subjects either passively listened to single-speaker stories, or selectively attended to a male or a female speaker in temporally-overlaid stories in separate experiments. Spectral, articulatory, and semantic models of the natural stories were constructed. Intrinsic selectivity profiles were identified via voxelwise models fit to passive listening responses. Attentional modulations were then quantified based on model predictions for attended and unattended stories in the cocktail-party task. We find that attention causes broad modulations at multiple levels of speech representations while growing stronger towards later stages of processing, and that unattended speech is represented up to the semantic level in parabelt auditory cortex. These results provide insights on attentional mechanisms that underlie the ability to selectively listen to a desired speaker in noisy multi-speaker environments.

neuroscience↗

Biased competition in semantic representation during natural visual search

Humans divide their attention among multiple visual targets in daily life, and visual search gets more difficult as the number of targets increases. The biased competition hypothesis (BC) has been put forth as an explanation for this phenomenon. BC suggests that brain responses during divided attention are a weighted linear combination of the responses during search for each target individually. Furthermore, this combination is biased by the intrinsic selectivity of cortical regions. Yet, it is unknown whether attentional modulations of semantic representations of cluttered and dynamic natural scenes are consistent with this hypothesis. Here, we investigated whether BC accounts for semantic representation during natural category-based visual search. Human subjects viewed natural movies, and their whole-brain BOLD responses were recorded while they attended to \"humans\", \"vehicles\" (i.e. single-target attention tasks), or \"both humans and vehicles\" (i.e. divided attention) in separate runs. We computed a voxelwise linearity index to assess whether semantic representation during divided attention can be modeled as a weighted combination of representations during the two single-target attention tasks. We then examined the bias in weights of this linear combination across cortical ROIs. We find that semantic representations during divided attention are linear to a substantial degree, and that they are biased toward the preferred target in category-selective areas across ventral temporal cortex. Taken together, these results suggest that the biased competition hypothesis is a compelling account for attentional modulations of semantic representation across cortex.\n\nSignificance Statement\n\nNatural vision is a complex task that involves splitting attention between multiple search targets. According to the biased competition hypothesis (BC), limited representational capacity of the cortex inevitably leads to a competition among representation of these targets and the competition is biased by intrinsic selectivity of cortical areas. Here we examined BC for semantic representation of hundreds of object and action categories in natural movies. We observed that: 1) semantic representation during simultaneous attention to two object categories is a weighted linear combination of representations during attention to each of them alone, and 2) the linear combination is biased toward semantic representation of the preferred object category in strongly category-selective areas. These findings suggest BC as a compelling account for attentional modulations of semantic representation across cortex in natural vision.

neuroscience↗