Biology subjects

Gottfried, J. A.

Publications and source records attributed to Gottfried, J. A..

4 recordsLinked to original sources

bioRxiv2026

MR KLEAN: a Generalized Acquisition-agnostic LLR k-Space Denoising Method for High-dimensional Imaging

PurposeHigh-dimensional and dynamic MRI are often limited by thermal noise, particularly in accelerated acquisitions. Although image-domain low-rank denoising methods (e.g., MP-PCA and NORDIC) are effective, their reliance on stationary noise distributions limits applicability to non-Cartesian sampling and advanced reconstructions. This work introduces Magnetic Resonance K-space Local low-rank Estimation for Attenuating Noise (MR KLEAN), a k-space low-rank denoising framework agnostic to acquisition trajectory and reconstruction strategy. Theory and MethodsMR KLEAN exploits local low-rank structure in multichannel, high-dimensional k-space. Data are prewhitened using a noise-only scan to enforce independent and identically distributed, zero-mean, unit-variance noise. Casorati matrices from local k-space patches are denoised by singular-value thresholding, with thresholds set via Monte-Carlo simulations under known noise statistics. MR KLEAN was evaluated in (1) a Cartesian 3D FLASH phantom study, (2) an ASL study with spiral readout and compressed sensing reconstruction to assess generalizability and preservation of temporal information via resting-state connectivity analysis, and (3) an accelerated cardiac cine study assessing performance under rapid temporal dynamics. ResultsMR KLEAN increased SNR and CNR in phantom studies. In vivo ASL showed reduced noise in perfusion images, improved relative SNR, and substantially enhanced resting-state networks detection. In cardiac imaging, noise was reduced and delineation of fine anatomical features improved while temporal fidelity was preserved across cardiac phases. ConclusionMR KLEAN provides robust, acquisition- and reconstruction-agnostic k-space denoising, improving image quality and allowing flexible spatial-temporal trade-offs. Results further support that high-dimensional k-space data retain intrinsic local low-rank structure analogous to image-space despite temporal signal variations.

bioengineering↗

bioRxiv2024

Direct piriform-to-auditory cortical projections shape auditory-olfactory integration

In a real-world environment, the brain must integrate information from multiple sensory modalities, including the auditory and olfactory systems. However, little is known about the neuronal circuits governing how odors influence and modulate sound processing. Here, we investigated the mechanisms underlying auditory-olfactory integration using anatomical, electrophysiological, and optogenetic approaches, focusing on the auditory cortex as a key locus for cross-modal integration. First, retrograde and anterograde viral tracing strategies revealed a direct projection from the piriform cortex to the auditory cortex. Next, using in vivo electrophysiological recordings of neuronal activity in the auditory cortex of awake male or female mice, we found that odors modulate auditory cortical responses to sound. Finally, we used in vivo optogenetic manipulations during electrophysiology to demonstrate that olfactory modulation in auditory cortex, specifically, odor-driven enhancement of sound responses, depends on direct input from the piriform cortex. Together, our results identify a novel role of piriform-to-auditory cortical circuitry in shaping olfactory modulation in the auditory cortex, shedding new light on the neuronal mechanisms underlying auditory-olfactory integration. Significance StatementAll living organisms exist within multisensory environments, yet there is a lack in our understanding of how the brain integrates multisensory information. This work highlights a direct piriform-to-auditory cortical circuit governing auditory-olfactory integration. Our results shed new light on a relatively understudied area of multisensory research, promising a more robust understanding of how animals and humans perceive and interact within complex environments.

neuroscience↗

bioRxiv2024

Leveraging Multi-echo EPI to Enhance BOLD Sensitivity in Task-based Olfactory fMRI

Functional magnetic resonance imaging (fMRI) using blood-oxygenation-level-dependent (BOLD) contrast relies on gradient echo echo-planar imaging (GE-EPI) to quantify dynamic susceptibility changes associated with the hemodynamic response to neural activity. However, acquiring BOLD fMRI in human olfactory regions is particularly challenging due to their proximity to the sinuses where large susceptibility gradients induce magnetic field distortions. BOLD fMRI of the human olfactory system is further complicated by respiratory artifacts that are highly correlated with event onsets in olfactory tasks. Multi-echo EPI (ME-EPI) acquires gradient echo data at multiple echo times (TEs) during a single acquisition and can leverage signal evolution over the multiple echo times to enhance BOLD sensitivity and reduce artifactual signal contributions. In the current study, we developed a ME-EPI acquisition protocol for olfactory task-based fMRI and demonstrated significant improvement in BOLD signal sensitivity over conventional single-echo EPI (1E-EPI). The observed improvement arose from both an increase in BOLD signal changes through a T2*-weighted echo combination and a reduction in non-BOLD artifacts through the application of the Multi-Echo Independent Components Analysis (ME-ICA) denoising method. This study represents one of the first direct comparisons between 1E-EPI and ME-EPI in high-susceptibility regions and provides compelling evidence in favor of using ME-EPI for future task-based fMRI studies.

neuroscience↗

bioRxiv2023

Piriform cortex takes sides: temporally-segregated odor representations from ipsilateral and contralateral nostrils within a single sniff

The human olfactory system has two discrete channels of sensory input, arising from olfactory epithelia housed in the left and right nostrils. Here, we asked whether primary olfactory cortex (piriform cortex, PC) encodes odor information arising from the two nostrils as integrated or distinct stimuli. We recorded intracranial EEG signals directly from PC while human subjects participated in an odor identification task where odors were delivered to the left, right, or both nostrils. We analyzed the time-course of odor-identity coding using machine learning approaches, and found that uni-nostril odor inputs to the ipsilateral nostril are encoded [~]480 ms faster than odor inputs to the contralateral nostril on average. During naturalistic bi-nostril odor sampling, odor information emerged in two temporally segregated epochs with the first epoch corresponding to the ipsilateral and the second epoch corresponding to the contralateral odor representations. These findings reveal that PC maintains distinct representations of odor input from each nostril through temporal segregation, highlighting an olfactory coding scheme at the cortical level that can parse odor information across nostrils within the course of a single inhalation.

neuroscience↗