Biology subjects

Muukkonen, I.

Publications and source records attributed to Muukkonen, I..

6 recordsLinked to original sources

bioRxiv2026

Attention modulates neural representations of acoustic, categorical, and identity features in a task-dependent manner

The human auditory system represents sounds at multiple levels, from low-level acoustic features to abstract category- and object-level information. Although selective attention enables listening in complex natural soundscapes, it remains unclear which representational levels are modulated by attention and how this depends on scene structure. Using fMRI, representational similarity analysis, and cross-experiment decoding, we examined attentional modulation of auditory representations under three conditions 1) listening to isolated sounds, 2) attending to one of three overlapping sounds from different categories or 3) one of three overlapping sounds from the same category. We show that attentional modulation is task-dependent: when competing sounds could not be distinguished by category, attention enhanced low-level acoustic feature processing, whereas in cross-category scenes it targeted abstract category-level representations. Object-identity representations were modulated by attention across both scene types, with category-specific differences, demonstrating flexible, task-dependent targeting of auditory features.

neuroscience↗

bioRxiv2025

Attention modulates the geometry of auditory representations

Selective attention enables the brain to prioritize behaviourally relevant information in complex environments, yet its neural mechanisms remain unclear. Here, we combined fMRI with representational geometry analyses to examine how attention reshapes neural population codes during naturalistic sound scenes. Participants attended to individual sound objects presented either with distractors from different categories (three objects across, 3OA) or the same category (three objects within, 3OW). Attention attracted neural population responses in low-dimensional manifolds toward the representation of each object presented in isolation, consistent with a reorganization of high-dimensional representational geometry. This effect depended on acoustic context: in 3OA, attended representations were significantly closer to object-alone representations than to distractors, whereas in 3OW attentional modulation was minimal. Category-specific effects were observed, with speech engaging left-lateralized language regions beyond the auditory cortex. Finally, stronger behavioural performance predicted greater representational attraction. These findings show that selective attention reshapes neural geometry in a context- and category-dependent manner closely linked to behaviour.

neuroscience↗

bioRxiv2025

Selective attention network in naturalistic auditory scenes is object and scene specific

Everyday auditory scenes often contain overlapping sound objects, requiring selective attention to isolate relevant objects from irrelevant background objects. This study examined how selective attention shapes neural representations of naturalistic sound scenes in the auditory cortex (AC). Using functional magnetic resonance imaging, we recorded brain activity from participants (n = 20) as they attended to a designated object in scenes comprising three overlapping sounds. Scenes were constructed in two manners: one where each object belonged to a different category (speech, animal, instrument) and another where all objects were from the same category. Attending to speech consistently enhanced activations in lateral AC subfields, while attention to animal and instrument sounds preferentially modulated medial subfields, supporting models where attention modulates feature-selective neural gain in AC. Remarkably, however, spatial pattern analysis revealed that the attended object dominated the AC activation patterns of the entire scene in a manner depending on both object type and scene composition: When the objects of the scene belonged to different categories, attended objects dominated fields processing higher-level category-specific features. In contrast, when all scene objects shared the same category, dominance shifted to fields processing low-level acoustic features. Thus, attention seems to dynamically prioritize the features offering maximal contrast within a given context, emphasizing object-specific patterns in feature-similar scenes and category-level patterns in feature-diverse scenes. Our results support models where top-down signals not only modulate gain but also affect several steps of auditory scene decomposition and analysis - influencing stream segregation and gating of higher-level processing in a contextual manner, adapting to specific auditory environments.

neuroscience↗

bioRxiv2023

Entropy predicts early MEG, EEG and fMRI responses to natural images

To reduce the redundancy in the input, the human visual system employs efficient coding. Therefore, images with varying entropy (amount of information) should elicit distinct brain responses. Here, we show that a simple entropy model outperforms all current models, including many deep neural networks, in predicting early MEG/EEG and fMRI responses to visual objects. This suggests that the neural populations in the early visual cortex adapt to the information in natural images.

neuroscience↗

bioRxiv2021

Prolonged and distributed processing of facial identity in the human brain

The recognition of facial identity is essential for social interactions. Despite extensive prior fMRI and EEG/MEG research on the neural representations of familiar faces, we know little about the spatio-temporal dynamics of face identity information. Therefore, we applied a novel multimodal approach by fusing the neuronal responses recorded in an fMRI and an EEG experiment. We analyzed the neural responses to naturally varying famous faces and traced how face identity emerges over time in different areas of the brain. We found that image invariant face identity information prevails over an extended time period (from 150 to 810 ms after stimulus onset) in the representational geometry of a broadly distributed network of parietal, temporal, and frontal areas with overlapping temporal profiles. These results challenge the current hierarchical models of face perception and suggest instead concerted and parallel activation of multiple nodes in the brains identity coding network while processing information of familiar faces.

neuroscience↗

bioRxiv2019

Spatio-temporal dynamics of face perception

The temporal and spatial neural processing of faces have been studied rigorously, but few studies have unified these dimensions to reveal the spatio-temporal dynamics postulated by the models of face processing. We used support vector machine decoding and representational similarity analysis to combine information from different locations (fMRI), timepoints (EEG), and theoretical models. By correlating information matrices derived from pair-wise decodings of neural responses to different facial expressions (neutral, happy, fearful, angry), we found early EEG timepoints (110-150 ms) to match fMRI data from early visual cortex (EVC), and later timepoints (170 - 250 ms) to match data from occipital and fusiform face areas (OFA/FFA) and posterior superior temporal sulcus (pSTS). The earliest correlations were driven by information from happy faces, and the later by more accurate decoding of fearful and angry faces. Model comparisons revealed systematic changes along the processing hierarchy, from emotional distance and visual feature coding in EVC to coding of intensity of expressions in right pSTS. The results highlight the importance of multimodal approach for understanding functional roles of different brain regions.

neuroscience↗