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Kachlicka, M.

Publications and source records attributed to Kachlicka, M..

3 recordsLinked to original sources

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↗

Neural tracking of melodic prediction is pre-attentive

Musics ability to modulate arousal and manipulate emotions relies upon formation and violation of predictions. Music is often used to modulate arousal and mood while individuals focus on other tasks, suggesting that sophisticated musical prediction may be implicit and obligatory, operating regardless of attention. Here we investigated the role of attention in musical prediction by presenting participants simultaneously with a musical passage in one ear and an audiobook in the other. Participants were asked to attend to either speech or music to perform a recognition memory task. Musical prediction was investigated using a computational model of music which was trained on a corpus of Western music (long-term learning) and/or incrementally on each stimulus (short-term learning). While neural tracking of the acoustics of music, including encoding of note onset and pitch interval size, was enhanced by attention, musical prediction tracked the neural signal robustly regardless of attention. However, although neural tracking of long-term musical prediction based on previously-learned statistical patterns was unaffected by attention, tracking of short-term musical prediction learned from the structure of each stimulus was present only when the music was attended. Thus, attention is crucial for short-term musical learning and prediction but is not required for musical prediction based on long-term stylistic exposure.

neuroscience↗

Slow phase-locked endogenous modulations support selective attention to sound

To make sense of complex soundscapes, listeners must select and attend to task-relevant streams while ignoring uninformative sounds. One possible neural mechanism underlying this process is alignment of endogenous oscillations with the temporal structure of the target sound stream. Such a mechanism has been suggested to mediate attentional modulation of neural phase-locking to the rhythms of attended sounds. However, such modulations are compatible with an alternate framework, where attention acts as a filter that enhances exogenously-driven neural auditory responses. Here we attempted to adjudicate between theoretical accounts by playing two tone steams varying across condition in tone duration and presentation rate; participants attended to one stream or listened passively. Attentional modulation of the evoked waveform was roughly sinusoidal and scaled with rate, while the passive response did not. This suggests that auditory attentional selection is carried out via phase-locking of slow endogenous neural rhythms.

neuroscience↗