Biology subjects

Dick, F.

Publications and source records attributed to Dick, F..

At least 19 recordsLinked to original sources

bioRxiv2026

An adolescent neuroimaging database combining movie-watching, eye-tracking and cognitive tasks

Adolescence is a critical period of neurodevelopment, yet most neuroimaging datasets focus on adult populations, leaving a gap in our understanding of how the brain processes information during this formative stage. Here we present a multimodal neuroimaging dataset acquired from 41 adolescent participants aged 11-18 years, combining 3T fMRI data with concurrent eye-tracking and physiological monitoring during naturalistic movie-watching. Data are shared in BIDS-compliant format and technical validation demonstrates good data quality across participants, with low head motion and strong inter-subject neural synchronisation during movie-watching. In addition to the scanning session, participants completed remote assessments covering a broad range of self-reported developmental and mental health traits, alongside cognitive tasks targeting reward-based and social learning. This dataset offers a rich resource for studying the adolescent brain, with particular utility for research on individual differences in mental health and cognition. All data and processing code is openly available to facilitate reproducible science.

neuroscience↗

bioRxiv2026

Global structure of new relational knowledge networks is represented in retrosplenial complex, and node-distance in hippocampus

Much of our knowledge is structured in networks, but how the brain represents such networks remains unclear. In most nested knowledge structures a subset of the nodes will be highly connected to other nodes in the network. High levels of connection can exist either locally (high degree centrality) or at a global level (high closeness/betweenness centrality). Here, we explored how the human brain represents network structure using functional magnetic resonance imaging (fMRI) and a novel learning paradigm. During training, participants learned the transition structure for travel between a set of fictious partially connected alien planets. Despite encountering only individual connections, participants choices indicated they could infer the broader network structure. Next day, they viewed each stimulus during a cover task while undergoing fMRI. Representational-similarity analysis showed that shortest-path distances within the learned graph were encoded in the posterior hippocampus and right retrosplenial complex, whereas global connectivity (closeness/ betweenness centrality) was represented in the left retrosplenial complex. These findings extend the view that brain networks associated with spatial navigation also process abstract relational knowledge using principles akin to mapping physical space. The results are also consistent with proposals that the hippocampus represents distance information and that the retrosplenial cortex acts as hub for integrating recently acquired knowledge.

neuroscience↗

bioRxiv2026

Revisiting the auditory hemodynamic response function in the era of fast fMRI

Recent advances in fast fMRI now enable whole-brain imaging with a TR of [≤]1 s, which has helped to rekindle interest in characterizing the blood oxygen level dependent hemodynamic response function (BOLD HRF). Recent studies in the visual system have found intra-areal differences in temporal response characteristics, as well as HRFs that were faster and narrower than predicted by standard models. The auditory system presents a unique challenge, in that neuronal populations must operate across timescales of microseconds to minutes, and the surface of auditory cortex in particular is intricately and heavily vascularized. Here, we used fast fMRI to characterise voxelwise auditory HRFs evoked by short naturalistic sounds, assessing HRF reproducibility and variability across sessions, participants, and independent datasets. Across two studies at 3 T, participants passively listened to short environmental sounds while fMRI and quantitative MRI data were acquired with a 1s TR. Voxelwise HRFs were estimated via novel cross-session alignment routine, and exclusion of large vascular contributions. We identified a diverse set of hemodynamically plausible response shapes, which were not consistently captured by standard HRF approaches. These responses were reproducible within participants across sessions and robust across two independent acquisitions. Using data-driven gamma models, we achieved stable estimates with relatively few runs, particularly in auditory temporal regions. Within auditory cortex, we observed reproducible spatial gradients in response timing and shape, with faster and higher magnitude responses in medial regions, and slower and lower magnitude responses laterally. Together, these findings demonstrate that auditory HRFs are diverse, reliable, and regionally specific, and highlight the value of fast fMRI and data-driven modelling for advancing interpretation of fMRI data.

neuroscience↗

bioRxiv2026

AutoNeuro: An Open-Source fMRI Toolbox for Real-Time Neuroadaptive Task Design

Real-time functional magnetic resonance imaging (fMRI) offers a powerful means of studying brain function adaptively, enabling experimental parameters to be updated dynamically in response to ongoing neural activity. However, current approaches remain limited by complex infrastructure requirements, bespoke implementations, and a lack of flexible frameworks for closed-loop neuroimaging, with many primarily focusing on neurofeedback experimental designs. Here we present AutoNeuro, an open-source framework for real-time fMRI acquisition, preprocessing, feature extraction, and adaptive experimental control. AutoNeuro connects directly to the MRI scanner, receiving reconstructed slices as soon as they become available, and streams them into a modular analysis pipeline designed for low-latency processing. Neural features are estimated at the temporal resolution of acquisition and are passed to a Bayesian optimisation agent that selects task conditions to maximise a user-defined objective function. Experimental conditions are represented within a bounded "experiment space", allowing heterogeneous conditions to be explored within a common coordinate system. We demonstrate AutoNeuro in a real-time fMRI experiment in which the system adaptively sampled task conditions to obtain a continuous map of brain response to the range of conditions contained within the experimental space. The system operated within the temporal constraints of real-time preprocessing and analysis, maintaining stable model estimates across iterations, converging on experimental conditions most relevant to the measured brain metric. These results establish AutoNeuro as a flexible platform for closed-loop neuroimaging, supporting hypothesis-driven optimisation as well as exploratory mapping of brain metrics across large experimental spaces.

neuroscience↗

bioRxiv2025

Attention to Psuedo-Tone Melodies Enhances Cortical but Not Brainstem Responses in Humans

Auditory selective attention, the ability to focus on specific sounds while ignoring competitors, enables communication in complex soundscapes. Though attention clearly modulates cortical responses to sound, whether and where this modulation occurs in subcortical structures remains disputed. Here, we use electroencephalography to record cortical and subcortical (auditory brainstem responses, ABRs) activity during a selective attention task. Human participants attend to a 3-note melody in one pitch range presented to one ear while ignoring a competing, interleaved melody in a different pitch range played to the other ear (Laffere et al., 2020, 2021). The melodies consist of pitch-evoking pseudo-tones formed by convolving a periodic impulse train with a brief tone pip. These stimuli allow us to measure both ABRs (elicited by each individual tone pip within a pseudo-note) and cortical responses (elicited by the onsets of pseudo-notes) simultaneously. We observed robust ABRs, but no evidence of modulation by attention. Conversely, cortical responses, measured by event related potentials (ERPs), demonstrated attentional modulation of the P1-N1 peak. We conclude that attentional modulation within the brainstem is not measurable in the well-defined peaks of the ABR, which themselves reflect processing up to the input stage to the inferior colliculus.

neuroscience↗

bioRxiv2025

Glycosylated diterpenes associate with early containment of Fusarium culmorum infection across wheat (Triticum aestivum L.) genotypes under field conditions

Wheat (Triticum aestivum L.) is severely affected by head blight, a destructive disease caused primarily by Fusarium species, which reduces yield and contaminates grains with trichothecene mycotoxins that compromise food and feed safety worldwide. Mechanistic insights into host-pathogen interactions have largely emerged from controlled experimental settings, providing conceptual foundations under conditions of constrained genetic and environmental complexity. Resolving consistent, generalizable molecular patterns across diverse wheat genotypes within a large-scale, heterogeneous field study remains technically and methodologically challenging. Addressing this gap, we integrated quantitative mycotoxin profiling with untargeted metabolomics in a field experiment comprising 105 wheat genotypes deliberately inoculated with F. culmorum, with the goal of identifying molecular signatures of infection and containment under realistic agronomic conditions. Quantified deoxynivalenol (DON) concentrations provided a robust, continuous measure of infection intensity, enabling metabolite profiles to be related directly to pathogen activity beyond the limitations of symptom-based visual scoring. Consistent with established Fusarium trichothecene biosynthesis, sesquiterpene-derived metabolites closely tracked toxin accumulation, thereby recapitulating infection-associated metabolic patterns across the large-scale field study. Conversely, glycosylated diterpene conjugates were elevated under low toxin accumulation, linking their abundance to contained Fusarium pathogen activity and highlighting a largely underexplored aspect of wheat metabolism in host-pathogen interactions. Elucidating their biosynthetic origin, enzymatic interconversion, and regulatory context will be key to defining potential diterpene-associated defense processes across wheat genotypes.

plant biology↗

bioRxiv2025

Auditory Cortical Gradients Integrate Bottom-Up and Top-Down Structure During Natural Sound Categorisation

Understanding how the brain organises natural categories is a central challenge in neuroscience. While prior work has shown that categories can be decoded from distributed activity patterns in auditory cortex, it remains unclear how these categories are globally arranged relative to one another, and how low-level acoustic and higher-level semantic structure jointly shape this organisation. Here, we addressed these questions by deriving low-dimensional functional gradients from high-depth functional magnetic resonance imaging (fMRI) data (three participants, [~]4.7 hours each) acquired during a category-specific one-back task. These gradients captured the principal axes of population activity in auditory cortex. Gradient-based models of the auditory cortex explained category structure more accurately than region-of-interest or whole-brain approaches, revealing that category information is distributed across multiple continuous axes rather than aligned with any single organisational dimension. Projecting acoustic (gammatone filter-bank) and behavioural similarity spaces directly into a shared framework with the fMRI functional axes showed that both contribute to the brains category geometry, with acoustic structure exerting a somewhat stronger influence. However, representational relationships varied across category pairs: some reflected primarily acoustic similarity, others semantic distinctions, and many a combination of both. This pairwise heterogeneity shows how auditory cortex may integrate multiple representational dimensions that define higher-level categories. Significance StatementCategorising natural sounds requires the brain to transform diverse acoustic signals into meaningful concepts. How this is achieved remains unclear: prior work has shown distributed activation patterns in auditory cortex, but not how category relationships are organised within its functional architecture. We show that natural sound categories are embedded across continuous cortical gradients that integrate bottom-up acoustic structure with top-down semantic information. Different categories emerge as flexible combinations of these spectral and behavioural dimensions. These findings reveal that natural sound categorisation arises from the geometry of cortical organisation, moving beyond localist accounts and offering a new framework for understanding how perception and cognition are linked in the human auditory system.

neuroscience↗

bioRxiv2025

A neuroimaging database combining movie-watching, eye-tracking, sensorimotor mapping, and cognitive tasks

We provide a multimodal naturalistic neuroimaging database (NNDb-3T+), designed to support the study of brain function under both naturalistic and controlled experimental conditions. The database includes high-quality 3T fMRI data from 40 participants acquired during full-length movie-watching and three sensory mapping tasks: somatotopy, retinotopy, and tonotopy. Each participant also completed synchronised eye-tracking during movie-watching and retinotopy, physiological recordings, and a battery of behavioural and cognitive assessments. Data were collected across two MRI sessions and a remote testing session, with all data organised in a BIDS-compliant format. Technical validation confirms high data quality, with minimal head motion, accurate eye-tracker calibration, and robust task-evoked activation patterns. The database provides a unique resource for investigating individual differences, functional topographies, multimodal integration, and naturalistic cognition. All raw and preprocessed data, quality metrics, and preprocessing scripts are publicly available to support reproducible research.

neuroscience↗

bioRxiv2025

Spatial coding supports auditory conceptual navigation

Grid cells in human entorhinal cortex encode spatial layouts for real-world navigation, yet their role in conceptual navigation remains unclear. Here we show that mentally transforming tones within a purely auditory pitch-duration space engages spatial circuits, and that such resources are causally necessary. In Experiment 1, participants trained for five days to navigate through a purely conceptual pitch-duration auditory space, then underwent fMRI on Day 6. We observed a six-fold modulation of entorhinal BOLD signals aligned to each participants trajectory angles, similar to grid-cell firing in physical space. Stronger grid-like coding predicted larger training-related gains. In Experiment 2, a new cohort performed the same task under either a spatial or non-spatial interference load. Only the spatial condition selectively disrupted performance on trials requiring mental "movement," indicating a causal reliance on spatial resources. These findings provide evidence that auditory conceptual transformations recruit--and depend on--spatial grid-like computations in the entorhinal-hippocampal system, pointing to a domain-general role for spatial coding in organizing new knowledge along continuous dimensions.

neuroscience↗

bioRxiv2024

An fMRI-based Approach for Measuring Contrast Sensitivity Across the Visual Field in Visual Cortex

Peripheral vision is crucial for daily activities and quality of life, yet traditional measures of visual function like visual acuity primarily assess central vision. Visual field tests can evaluate peripheral vision but require extended focus combined with precise fixation, often very challenging for patients with severe sight loss. Functional MRI (fMRI) with population receptive field (pRF) mapping offers a non-invasive way to map scotomas but is limited by its reliance on single contrast levels and the necessity of accurate fixation. We developed an fMRI-based approach to measure contrast sensitivity across the visual field without the need for precise fixation. By combining large-field stimulation with varying spatial frequencies and contrast levels with either pRF mapping or a retinotopic atlas based on anatomical landmarks, we modeled contrast sensitivity in the primary visual cortex (V1) over a large (40 deg) expanse of the visual field. In seven normal-sighted participants, we characterized differences in V1 cortical sensitivity across eccentricities and visual quadrants, finding reliable and reproducible patterns of sensitivity differences at individual and session levels. To assess the methods tolerance to fixation variability, we further investigated how different levels of eye movement affect cortical sensitivity patterns in two participants. We found that cortical sensitivity patterns were largely preserved across eye movement, particularly at low spatial frequencies. This suggests that our approach can accommodate several degrees of fixation instability, making it suitable for populations with unstable or biased fixation for whom visual field maps are harder to acquire behaviorally (e.g., patients with dense central scotoma or strabismus). Additionally, our method effectively visualized cases of simulated and disease-linked sensitivity loss at the cortical level. Crucially, we demonstrated that these results could be largely recovered using a structure-based retinotopic atlas, eliminating the need for pRF mapping and precise fixation - although such an approach reduced sensitivity. This approach, integrating large-field stimulation with a retinotopic atlas, offers a promising tool for monitoring vision loss and recovery in patients with various visual impairments, addressing a significant challenge in current clinical assessments.

neuroscience↗

bioRxiv2024

Systematic changes in neural selectivity reflect the acquired salience of category-diagnostic dimensions

Humans and other animals develop remarkable perceptual and cognitive specializations for identifying, differentiating, and acting on classes of ecologically important signals. This expertise is flexible enough to support diverse perceptual judgments: a voice, for example, simultaneously conveys what a talker says, as well as myriad cues about her identity and state. Expert perception across complex signals thus involves discovering and learning regularities that best inform diverse perceptual judgments, as well as weighting this information flexibly as task demands change. Here, we test whether this flexibility may involve endogenous attentional gain. We use two prospective auditory category learning tasks to relate a complex, entirely novel soundscape to four classes of "alien identity" and two classes of "alien size." Identity, but not size, categorization requires discovery and learning of patterned acoustic input situated in one of two simultaneous, non-overlapping frequency bands. This allows us to capitalize on the coarsely segregated frequency-band-specific channels tiling auditory cortex, using fMRI to ask whether category-relevant perceptual information present in one frequency band is prioritized relative to simultaneous, uninformative information in the other frequency band. Among participants expert at alien identity categorization, we observe prioritization of the identity-diagnostic frequency band that persists even when the diagnostic information becomes irrelevant in the size categorization task. Tellingly, the neural selectivity evoked implicitly in the identity categorization task aligns with that in an independent task, where activation is driven by explicit and sustained selective attention to pure tones in one or the other frequency band. Additionally, the learning trajectories taken to achieve expert-level categorization leave fingerprints on the patterns of neural activity associated with the diagnostic dimension. In all, this indicates that acquiring categories can drive the emergence of acquired attentional gain to category-diagnostic input dimensions.

neuroscience↗

bioRxiv2024

Distributional learning drives statistical deafening

Humans and other animals use information about how likely it is for something to happen. The absolute and relative probability of an event influences a remarkable breadth of behaviors, from foraging for food to comprehending linguistic constructions -- even when these probabilities are learned implicitly. It is less clear how, and under what circumstances, statistical learning of simple probabilities might drive changes in perception and cognition. Here, across a series of 29 experiments, we probe listeners sensitivity to task-irrelevant changes in the probability distribution of tones acoustic frequency across tone-in-noise detection and tone duration decisions. We observe that the task-irrelevant frequency distribution influences the ability to detect a sound and the speed with which perceptual decisions about its duration are made. The shape of the probability distribution, its range, and a tones relative position within that range impact observed patterns of suppression and enhancement of tone detection and decision making. Perceptual decisions are also modulated by a newly discovered perceptual bias, with lower frequencies in the distribution more often and more rapidly perceived as longer, and higher frequencies as shorter. Perception is sensitive to rapid distribution changes, but distributional learning from previous probability distributions also carries over. In fact, massed exposure to a single point along the dimension results in seemingly maladaptive loss of sensitivity - occurring entirely in the absence of feedback or reward - along a range of subsequently encountered frequencies. This points to a gain mechanism that suppresses sensitivity to regions along a perceptual dimension that are less likely to be encountered. Significance StatementOrganisms as diverse as honeybees and humans pick up on probabilities in the world around them. People implicitly learn the likelihood of a color, price range, or even syntactic structure. How does statistical learning affect how we detect events and make decisions, especially when probabilities are completely irrelevant to the task at hand, and can change without warning? We find that people learn and track changes in perceptual probabilities irrelevant to a task and that this learning drives dynamic shifts in perception characterized by graded effects of enhancement - and primarily - suppression across acoustic frequency. This can result in a remarkably long- lived diminishment of perceptual sensitivity that seems maladaptive but may instead reflect use of likelihood to guide and sharpen perception.

neuroscience↗

bioRxiv2024

EEG responses to rapidly unfolding stochastic sounds reflect precision tracking

The brain is increasingly viewed as a statistical learning machine, where our sensations and decisions arise from the intricate interplay between bottom-up sensory signals and constantly changing expectations regarding the surrounding world. Which statistics does the brain track while monitoring the rapid progression of sensory information? Here, by combining EEG (three experiments N[≥]22 each) and computational modelling, we examined how the brain processes rapid and stochastic sound sequences that simulate key aspects of dynamic sensory environments. Passively listening participants were exposed to structured tone-pip arrangements that contained transitions between a range of stochastic patterns. Predictions were guided by a Bayesian predictive inference model. We demonstrate that listeners automatically track the statistics of unfolding sounds, even when these are irrelevant to behaviour. Transitions between sequence patterns drove an increase of the sustained EEG response. This was observed to a range of distributional statistics, and even in situations where behavioural detection of these transitions was at floor. These observations suggest that the modulation of the EEG sustained response reflects a universal process of belief updating within the brain. By establishing a connection between the outputs of the computational model and the observed brain responses, we demonstrate that the dynamics of these transition-related responses align with the tracking of precision - the confidence or reliability assigned to a predicted sensory signal - shedding light on the intricate interplay between the brains statistical tracking mechanisms and its response dynamics.

neuroscience↗

bioRxiv2023

Netrin signaling mediates survival of dormant epithelial ovarian cancer cells

Dormancy in cancer is a clinical state in which residual disease remains undetectable for a prolonged duration. At a cellular level, rare cancer cells cease proliferation and survive chemotherapy and disseminate disease. We created a suspension culture model of high grade serous ovarian cancer (HGSOC) dormancy and devised a novel CRISPR screening approach to identify survival genes in this context. In combination with RNA-seq, we discovered the Netrin signaling pathway as critical to dormant HGSOC cell survival. We demonstrate that Netrin-1, -3, and its receptors are essential for low level ERK activation to promote survival, and that Netrin activation of ERK is unable to induce proliferation. Deletion of all UNC5 family receptors blocks Netrin signaling in HGSOC cells and compromises viability during the dormancy step of dissemination in xenograft assays. Furthermore, we demonstrate that Netrin-1 and -3 overexpression in HGSOC correlates with poor outcome. Specifically, our experiments reveal that Netrin overexpression elevates cell survival in dormant culture conditions and contributes to greater spread of disease in a xenograft model of abdominal dissemination. This study highlights Netrin signaling as a key mediator HGSOC cancer cell dormancy and metastasis.

cancer biology↗

bioRxiv2022

Salient sounds distort time perception and production

The auditory world is often cacophonous, with some sounds capturing attention and distracting us from our goals. Despite the universality of this experience, many questions remain about how and why sound captures attention, how rapidly behavior is disrupted, and how long this interference lasts. Here we use a novel measure of behavioral disruption to test two predictions made by models of auditory salience. First, models predict that goal-directed behavior is disrupted at points in time that feature a high degree of spectrotemporal change. We find that behavioral disruption is precisely time-locked to the onset of distracting sound events: participants tapping to a metronome speed up immediately after the onset of distractors. Moreover, this response is greater for more salient sounds (larger amplitude) and sound changes (greater pitch shift). Second, models predict that different auditory features are combined into an overarching salience map. We find that the time course of behavioral disruption is highly similar after acoustically disparate sound events, suggesting overlapping mechanisms of attentional capture: both sound onsets and pitch shifts of continuous background sounds speed responses at 750 ms, with these effects dying out by 1750 ms. These temporal distortions can be observed using only data from the first trial across participants. A potential mechanism underlying these results is that arousal increases after distracting sound events, leading to an expansion of time perception, and causing participants to misjudge when their next movement should begin. Significance StatementThe noisy world constantly challenges our pursuit of goals. When driving, for example, a cacophony of mechanical, musical, and conversational sounds surrounds us and can wrench our focus away from the road. While the physiological signatures of auditory attentional capture are well researched, we know surprisingly little about how sound affects moment-to-moment behavior: How quickly do sounds affect our actions, how transient is the effect, and how is action affected by changes in sound properties? Here we use a synchronized tapping paradigm to show that loud sounds and large acoustic changes cause rapid distortions in time perception. However, these distortions were corrected within 2 seconds, showing that goal-directed behavior is transiently vulnerable yet ultimately resilient in the face of distraction.

neuroscience↗

bioRxiv2022

Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis

Quantitative MRI (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (R1), effective transverse relaxation rate (R2*), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (R2* at 3T, R1 at 7T), endothelial cells (R1 and MTsat at 3T), microglia (R1 and MTsat at 3T, R1 at 7T), and oligodendrocytes (R1 at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types.

neuroscience↗

bioRxiv2021

Online tests yield robust thresholds with the right auditory hygiene

Most human auditory psychophysics research has historically been conducted in carefully controlled environments with calibrated audio equipment, and over potentially hours of repetitive testing with expert listeners. Here, we operationally define such conditions as having high auditory hygiene. From this perspective, conducting auditory psychophysical paradigms online presents a serious challenge, in that results may hinge on absolute sound presentation level, reliably estimated perceptual thresholds, low and controlled background noise levels, and sustained motivation and attention. We introduce a set of procedures that address these challenges and facilitate auditory hygiene for online auditory psychophysics. First, we establish a simple means of setting sound presentation levels. Across a set of four level-setting conditions conducted in person, we demonstrate the stability and robustness of this level setting procedure in open air and controlled settings. Second, we test participants tone-in-noise thresholds using widely adopted online experiment platforms and demonstrate that reliable threshold estimates can be derived online in approximately one minute of testing. Third, using these level and threshold setting procedures to establish participant-specific stimulus conditions, we show that an online implementation of the classic probe-signal paradigm can be used to demonstrate frequency-selective attention on an individual-participant basis, using a third of the trials used in recent in-lab experiments. Finally, we show how threshold and attentional measures relate to well-validated assays of online participants in-task motivation, fatigue, and confidence. This demonstrates the promise of online auditory psychophysics for addressing new auditory perception and neuroscience questions quickly, efficiently, and with more diverse samples. Code for the tests is publicly available through Pavlovia and Gorilla.

neuroscience↗

bioRxiv2021

Dimension-Selective Attention and Dimensional Salience Modulate Cortical Tracking of Acoustic Dimensions

Some theories of auditory categorization suggest that auditory dimensions that are strongly diagnostic for particular categories - for instance voice onset time or fundamental frequency in the case of some spoken consonants - attract attention. However, prior cognitive neuroscience research on auditory selective attention has largely focused on attention to simple auditory objects or streams, and so little is known about the neural mechanisms that underpin dimension-selective attention, or how the relative salience of variations along these dimensions might modulate neural signatures of attention. Here we investigate whether dimensional salience and dimension-selective attention modulate cortical tracking of acoustic dimensions. In two experiments, participants listened to tone sequences varying in pitch and spectral peak frequency; these two dimensions changed at systematically different rates. Inter-trial phase coherence (ITPC) and EEG signal amplitude at the rates of pitch and spectral change allowed us to measure cortical tracking of these dimensions. In Experiment 1, tone sequences varied in the size of the pitch intervals, while the size of spectral peak intervals remained constant. Neural entrainment to pitch changes was greater for sequences with larger compared to smaller pitch intervals, with no difference in entrainment to the spectral dimension. In Experiment 2, participants selectively attended to either the pitch or spectral dimension. Neural entrainment was stronger in response to the attended compared to unattended dimension for both pitch and spectral dimensions. These findings demonstrate that bottom-up and top-down attentional mechanisms enhance the cortical tracking of different acoustic dimensions within a single sound stream.

neuroscience↗