Biology subjects

Kahn, I.

Publications and source records attributed to Kahn, I..

10 recordsLinked to original sources

bioRxiv2026

Tasting from memory: reconstructing taste from visual cues in the human brain

Taste guides us toward nourishment and away from harm. Yet when we decide what to eat, taste only exists in memory, evoked by a cue. How the brain retrieves taste memories is almost entirely unknown. If memory re-creates experience, it should reproduce the brain's activation while tasting, even in the absence of taste. We scanned participants while they formed and then retrieved associations between tastes and visual cues. The gustatory cortex was engaged during retrieval and distinguished among remembered tastes, but not using the patterns it had formed while tasting. Patterns persisted instead in lateral parietal cortex, distinguishing individual tastes, not just taste-categories. Activity in the amygdala covaried with this same parietal region and amygdala activity predicted which associations were retained. Taste memory is not simply a re-creation of sensory experience, but a distinct representation, outside the taste system, yet specific enough to guide what we choose to eat.

neuroscience↗

bioRxiv2026

The Periaqueductal Gray Selectively Supports Reversal Learning During a Flexible Discrimination Task in Mice

Flexible, goal-directed behavior depends on the ability to update value representations in response to changing contingencies. This ability depends on distributed brain networks, calling for use of whole-brain imaging. Widely used in human research, whole-brain imaging in rodents has been a major challenge that has only recently been properly addressed. Using functional MRI in behaving mice performing a go/no-go odor discrimination task, we compared neural activity during initial cue-reward learning (acquisition) and subsequent contingency reversal. To link neural activity to underlying learning processes, we modeled value updating using a model-free reinforcement-learning algorithm. Trial-by-trial estimates of state-action values allowed us to dissociate acquisition from reversal-related signals, revealing that ventral striatal responses tracked expected value during acquisition, whereas reversal learning additionally recruited the periaqueductal gray (PAG), a midbrain structure classically linked to threat processing and aversive learning. PAG activity closely followed model-derived signatures of reversal learning, implicating it in the suppression of previously rewarded actions and in updating behavior in the absence of explicit punishment. These findings reveal a previously unrecognized computational role for the PAG in value-based decision-making and cognitive flexibility, and substantiate task-fMRI as a powerful tool to study the rodent brain at a mesoscale resolution.

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bioRxiv2025

Dopamine release effects on striatal blood oxygenation and whole brain plasticity underlying associative learning

Dopaminergic signaling in the nucleus accumbens (NAc) is central to reward-based learning, but its relationship to brain-wide hemodynamics remains unclear. Using concurrent fMRI and dopamine photometry in awake, behaving mice, we reveal that associative learning induces a gradual temporal shift in NAc blood oxygenation responses that mirrors dopamine release dynamics. This shift emerges with cue-reward learning and extends across a distributed network including prefrontal, insular, and hypothalamic regions. Further, dopamine transients tightly correspond with local BOLD signals, and variations in reward value modulate delayed BOLD responses in both the NAc and additional subcortical structures. Removing dopaminergic contributions abolishes this reward-related modulation, demonstrating that BOLD signals encode dopaminergic value prediction. These findings establish a mechanistic link between dopamine signaling and widespread neural plasticity during learning.

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bioRxiv2021

Structural brain connectivity predicts acute pain after mild traumatic brain injury

Mild traumatic brain injury, mTBI, is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute post-injury pain is important since it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 172 patients with mTBI, following a motorized vehicle collision and used a machine learning approach to extract white matter structural and resting state fMRI functional connectivity measures to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamic-cortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in two independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6-months after the collision still predicted mTBI pain at that timepoint (n = 36). These white-matter connections were associated with two nociceptive psychophysical outcomes tested at a remote body site - namely conditioned pain modulation and magnitude of suprathreshold pain-, and with pain sensitivity questionnaire scores. Our validated findings demonstrate a stable white-matter network, the properties of which determine a significant amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.

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bioRxiv2020

Structural and Functional Brain-wide Alterations in A350V IQSEC2 Mutant Mice Displaying Autistic-like Behavior

IQSEC2 is an X-linked gene which is associated with autism spectrum disorder (ASD), intellectual disability and epilepsy. IQSEC2 is a postsynaptic density protein, localized on excitatory synapses as part of the NMDA receptor complex and is suggested to play a role in AMPA receptor trafficking and mediation of long-term depression. Here, we present brain-wide structural volumetric and functional connectivity characterization in a novel mouse model with a missense mutation in the IQ domain of IQSEC2 (A350V). Using high-resolution structural and functional MRI, we show that animals with the A350V mutation display increased whole-brain volume which was further found to be specific to the cortex and hippocampus. Moreover, using a data-driven approach we demonstrate that A350V mice present alterations in structure-function relations of the frontal, auditory, and visual networks. Examination of these alterations revealed an increase in functional connectivity between the anterior cingulate cortex and the dorsomedial striatum. We also show that corticostriatal functional connectivity is correlated with individual variability in social behavior only in A350V mice, as assessed using the three-chamber social preference test. Our results at the systems-level bridge the impact of previously reported changes in AMPA receptor trafficking to network-level disruption and impaired social behavior. Further, the A350V mouse model recapitulates similarly reported brain-wide changes in other ASD mouse models, with substantially different cellular-level pathologies that nonetheless result in similar brain-wide alterations, suggesting that novel therapeutic approaches in ASD that result in systems-level rescue will be relevant to IQSEC2 mutations. Significance StatementSeveral recent studies have characterized the changes in the organization of brain networks in animal models of autism spectrum disorders (ASD). Here we assessed the effect of an A350V missense mutation in the IQSEC2 gene, which is associated with ASD, on brain-wide functional connectivity and its relation to social behavior deficits in A350V mice relative to controls. We found that the A350V IQSEC2 model results in disrupted functional connectivity of the anterior cingulate cortex and the dorsomedial striatum. Critically, disrupted increased corticostriatal functional connectivity is predictive of individual variability in social interaction only in A350V mice implicating this pathway in the pathophysiology of the A350V IQSEC2 mutation.

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bioRxiv2020

Brain-wide structural and functional disruption in mice with oligodendrocyte specific Nf1 deletion is rescued by inhibition of NOS

Neurofibromin gene (NF1) mutation causes Neurofibromatosis type 1 (NF1), a disorder in which brain white matter deficits identified by neuroimaging are common, yet of unknown cellular etiology. In mice, Nf1 loss in adult oligodendrocyte causes myelin decompaction, and increases oligodendrocyte nitric oxide (NO) levels. Nitric oxide synthase (NOS) inhibitors rescue this pathology. Whether oligodendrocyte pathology is sufficient to affect brainwide structure and account for NF1 imaging findings is unknown. Here, we show that Nf1 gene inactivation in adult oligodendrocytes (Plp-Nf1fl/+ mice) results in a motor coordination deficit. Magnetic resonance imaging in awake mice shows that fractional anisotropy is reduced in Plp-Nf1fl/+ corpus callosum and that interhemispheric functional connectivity in motor cortex is also reduced, consistent with disrupted myelin integrity. Further, NOS-specific inhibition rescued both measures. These results demonstrate that oligodendrocyte defects account for aspects of brain dysfunction in NF1, which can be identified by neuroimaging and ameliorated by NOS inhibition. Significance statementThis study assesses the effects of myelin decompaction on motor behavior and brain-wide structural and functional connectivity, and the effect of nitric oxide synthase (NOS) inhibition by N-nitro-L-arginine methyl ester (L-NAME) on these imaging measures. We report that inducible oligodendrocyte-specific inactivation of the Nf1 gene, which causes myelin decompaction, results in reduced motor coordination. Using diffusion-based MRI we show reduced myelin integrity and using functional MRI we show reduced functional connectivity in awake passive mice. L-NAME administration results in rescue of the pathology at the mesoscopic level using imaging procedures that can be directly applied to humans to study treatment efficacy in clinical trials.

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bioRxiv2020

Individual variability in functional connectivity architecture of the mouse brain

The functional organization of brain networks can be estimated using fMRI by examining the coherence of spontaneous fluctuations in the fMRI signal, a method known as resting-state functional connectivity MRI. Previous studies in humans reported that such functional networks are dominated by stable group and individual factors, demonstrating that fMRI is suited to measuring subject-specific characteristics, and suggesting the utility of such precision fMRI approach in personalized medicine. However, mechanistic investigations to the sources of individual variability in health and disease are limited in humans and thus require animal models. Here, we used repeated-measurement resting-state fMRI in awake mice to quantify the contribution of individual variation to the functional architecture of the mouse cortex. Comparing the organization of functional networks across the group, we found dominant common organizational principles. The data also revealed stable individual features, which create a unique fingerprint that allow identification of individual mice from the group. Examining the distribution of individual variation across the mouse cortex, we found it is homogeneously distributed in both sensory and association networks. Finally, connectome-based predictive modeling of motor behavior in the rotarod task revealed that individual variation in functional connectivity explained behavioral variability. Collectively, these results show that mouse functional networks are characterized by individual variations suggesting that individual variation characterizes the mammalian cortex in general, and not only the primate cortex. These findings lay the foundation for future mechanistic investigations of individual brain organization and pre-clinical studies of brain disorders in the context of personalized medicine.

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bioRxiv2019

Structural integrity following focused ultrasound thalamotomy and its correlation with tremor relief

BackgroundMagnetic-resonance-guided focused ultrasound ablation of ventral intermediate nucleus of the thalamus is a new treatment for tremor disorders.\n\nObjectivesWe sought to evaluate the white matter integrity prior to and following focused ultrasound ablation and its correlation with clinical outcome.\n\nMethods22 patients with essential tremor and 17 patients with Parkinsons disease underwent tremor and quality-of-life assessments prior to and at one and six months following focused ultrasound ablation. All patients underwent MRI including T1, T2-FLAIR and diffusion weighted imaging before treatment and at one day, 7-10 days, 1-3 months, and 6 months or more following it. Diffusivity parameters were calculated and fiber tractography measures were extracted. Change in diffusivity parameters were assessed inside the ablated core, in the motor thalamus and throughout the dentato-rubro-thalamo-cortical tract.\n\nResultsWe found short-term changes in the motor thalamus and in the tract between the thalamus and regions within the dentato-rubro-thalamo-cortical tract. Long term damage was found in the ablated core and in the tract connecting the thalamus and red-nucleus. Inverse correlation was found between fractional anisotropy in the motor thalamus one day following ablation and tremor improvement in both patient groups, with lower values before treatment associated with better outcome (tremor relief) in essential tremor patients.\n\nConclusionsShort-and long-term changes in white matter integrity are present following focused ultrasound thalamotomy. Regions demonstrating long-term white matter changes may be responsible for the tremor relief seen in patients, implicating these regions in the disorders pathogenesis.

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bioRxiv2019

Loss of function in the autism and learning disabilities associated gene Nf1 disrupts corticocortical and corticostriatal functional connectivity in human and mouse

Children with the autosomal dominant single gene disorder, neurofibromatosis type 1 (NF1), display multiple structural and functional changes in the central nervous system, resulting in neuropsychological cognitive abnormalities. Here we assessed the pathological functional organization that may underlie the behavioral impairments in NF1 using resting-state functional connectivity MRI. Coherent spontaneous fluctuations in the fMRI signal across the entire brain were used to interrogate the pattern of functional organization of corticocortical and corticostriatal networks in both NF1 pediatric patients and mice with a heterozygous mutation in the Nf1 gene (Nf1+/-). Children with NF1 demonstrated abnormal organization of cortical association networks and altered posterior-anterior functional connectivity in the default network. Examining the contribution of the striatum revealed that corticostriatal functional connectivity was altered. NF1 children demonstrated reduced functional connectivity between striatum and the frontoparietal network and increased striatal functional connectivity with the limbic network. Awake passive mouse functional connectivity MRI in Nf1+/- mice similarly revealed reduced posterior-anterior connectivity along the cingulate cortex as well as disrupted corticostriatal connectivity. The striatum of Nf1+/- mice showed increased functional connectivity to somatomotor and frontal cortices and decreased functional connectivity to the auditory cortex. Collectively, these results demonstrate similar alterations across species, suggesting that NF1 pathogenesis is linked to striatal dysfunction and disrupted corticocortical connectivity in the default network.

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bioRxiv2019

Individual structural features constrain the functional connectome

Whole brain dynamics intuitively depends upon the internal wiring of the brain; but to which extent the individual structural connectome constrains the corresponding functional connectome is unknown, even though its importance is uncontested. After acquiring structural data from individual mice, we virtualized their brain networks and simulated in silico functional MRI data. Theoretical results were validated against empirical awake functional MRI data obtained from the same mice. We demonstrate that individual structural connectomes predict the functional organization of individual brains. Using a virtual mouse brain derived from the Allen Mouse Brain Connectivity Atlas, we further show that the dominant predictors of individual structure-function relations are the asymmetry and the weights of the structural links. Model predictions were validated experimentally using tracer injections, identifying which missing connections (not measurable with diffusion MRI) are important for whole brain dynamics in the mouse. Individual variations thus define a specific structural fingerprint with direct impact upon the functional organization of individual brains, a key feature for personalized medicine.\n\nSIGNIFICANCE STATEMENTThe structural connectome is a key determinant of brain function and dysfunction. The connectome-based model approach aims to understand the functional organization of the brain by modeling the brain as a dynamical system and then studying how the functional architecture rises from the underlying structural skeleton. Here, taking advantage of mice studies, we systematically investigated the informative content of different structural features in explaining the emergence of the functional ones. We demonstrate that individual variations define a specific structural fingerprint with a direct impact upon the functional organization of individual brains stressing the importance of using individualized models to understand brain function. We show how limitations of connectome reconstruction with the diffusion-MRI method restrict our comprehension of the structural-functional relation.

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