Biology subjects

Hakonen, M.

Publications and source records attributed to Hakonen, M..

6 recordsLinked to original sources

bioRxiv2026

Volitional hand activation intensifies cortical proprioceptive processing in the primary sensorimotor cortex

Proprioception refers to the sense of position and movement of the body and is essential for the planning and execution of movements, especially skilled hand movements. The somatotopic organization of the fingers in the human sensorimotor (SM1) cortex has previously been studied using passive tactile stimulation and active movements. However, the finger representations in response to proprioceptive stimulation in the SM1 cortex are incompletely understood. To address this, we investigated cortical representations of the index and ring fingers during kinematically matched passive and active finger movements using 3T fMRI and an MRI-compatible proprioceptive stimulator. Both active and passive conditions elicited significant activations in the SM1 cortex, with stronger and more extensive responses observed during the active condition. The results indicated that volitional activation of the fingers intensifies cortical proprioceptive processing in the SM1 cortex. This observation could be explained by the active state of the SM1 cortex and the increased sensitivity of peripheral proprioceptors during the active condition. Key pointsVolitional activation of the fingers intensifies cortical processing of proprioceptive afference and modulates the organization of finger representations in the SM1 cortex. This could be explained by the active state of the SM1 cortex and the increased sensitivity of peripheral proprioceptors during the active condition. Proprioceptive finger representations followed the classical somatotopic organization at the group level, although this organization was not consistently observed across all subjects.

neuroscience↗

bioRxiv2025

Function of the auditory cortex characterized by its intrinsic dynamic coactivation patterns estimated in individuals

Determining the functional organization of the auditory cortex (AC) has been difficult with conventional task-based approaches due to the broad responsiveness of auditory subregions to various acoustic properties. Moreover, most studies have investigated functional organization of AC with static methods, although brain has shown to be organized into dynamic networks. Here, we investigated dynamically varying coactivation patterns of the local networks in the auditory cortex (AC) determined from 7T fMRI data with a novel individualized network-based algorithm. An eight-pattern solution was selected for closer examination based on its high reproducibility of the occurrence rates (r=0.86) and the spatial topography (r=0.79) between sessions. Dynamic AC patterns successfully captured interindividual variability, as indicated by significantly higher variability between than within individuals for the AC pattern occurrence rates and spatial topographies. The coactivation patterns shared similarities between resting-state and auditory-task data, as indicated by the group-level similarity of 0.84 and individual-level similarity of 0.71 in the spatial topographies. Furthermore, the occurrence rates of AC patterns identified in the task data, using pattern templates derived from resting-state data, correlated with specific task contrast regressors. Our results indicate that the AC function can be characterized by a set of dynamically varying coactivation patterns that are consistently observed during resting state and auditory stimulation, and that get synchronized with auditory input. These findings enhance our understanding of the relationship between spontaneous and stimulus-driven activity in the AC and support the development of more time-efficient paradigms for studying its functional organization.

neuroscience↗

bioRxiv2024

Individual connectivity-based parcellations reflect functional properties of human auditory cortex

Neuroimaging studies of the functional organization of human auditory cortex have focused on group-level analyses to identify tendencies that represent the typical brain. Here, we mapped auditory areas of the human superior temporal cortex (STC) in 30 participants by combining functional network analysis and 1-mm isotropic resolution 7T functional magnetic resonance imaging (fMRI). Two resting-state fMRI sessions, and one or two auditory and audiovisual speech localizer sessions, were collected on 3-4 separate days. We generated a set of functional network-based parcellations from these data. Solutions with 4, 6, and 11 networks were selected for closer examination based on local maxima of Dice and Silhouette values. The resulting parcellation of auditory cortices showed high intraindividual reproducibility both between resting state sessions (Dice coefficient: 69-78%) and between resting state and task sessions (Dice coefficient: 62-73%). This demonstrates that auditory areas in STC can be reliably segmented into functional subareas. The interindividual variability was significantly larger than intraindividual variability (Dice coefficient: 57%-68%, p<0.001), indicating that the parcellations also captured meaningful interindividual variability. The individual-specific parcellations yielded the highest alignment with task response topographies, suggesting that individual variability in parcellations reflects individual variability in auditory function. Connectional homogeneity within networks was also highest for the individual-specific parcellations. Furthermore, the similarity in the functional parcellations was not explainable by the similarity of macroanatomical properties of auditory cortex. Our findings suggest that individual-level parcellations capture meaningful idiosyncrasies in auditory cortex organization.

neuroscience↗

bioRxiv2023

Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI

In graph theory, "multilayer networks" represent systems involving several interconnected topological levels. One example in neuroscience is the stratification of connections between different cortical depths or "laminae", which is becoming non-invasively accessible in humans using ultra-high-resolution functional MRI (fMRI). Here, we applied multilayer graph theory to examine functional connectivity across different cortical depths in humans, using 7T fMRI (1-mm3 voxels; 30 participants). Blood oxygenation level dependent (BOLD) signals were derived from five depths between the white matter and pial surface. We compared networks where the inter-regional connections were limited to a single cortical depth only ("layer-by-layer matrices") to those considering all possible connections between areas and cortical depths ("multilayer matrix"). We utilized global and local graph theory features that quantitatively characterize network attributes including network composition, nodal centrality, path-based measures, and hub segregation. Detecting functional differences between cortical depths was improved using multilayer connectomics compared to the layer-by-layer versions. Superficial depths of the cortex dominated information transfer and deeper depths drove clustering. These differences were largest in frontotemporal and limbic regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information; thus, multilayer connectomics could provide a methodological framework for studies on how information flows across this stratification.

neuroscience↗

bioRxiv2021

More comprehensive proprioceptive stimulation of the hand amplifies its cortical processing

Corticokinematic coherence (CKC) quantifies the phase coupling between limb kinematics and cortical neurophysiological signals reflecting proprioceptive feedback to the primary sensorimotor (SM1) cortex. We studied CKC to proprioceptive stimulation (i.e. movement-actuator-evoked movements) of right-hand digits (index, middle, ring and little) performed simultaneously or separately. CKC was computed between magnetoencephalography (MEG) and finger acceleration signals. The strongest CKC was obtained by stimulating the fingers simultaneously at fixed 3-Hz frequency, and can, therefore, be recommended as design for fast functional localization of the hand area in the primary sensorimotor (SM1) cortex using MEG. The peaks of CKC sources were concentrated in the hand region of the SM1 cortex, but did not follow consistent somatotopic order. This result suggests that spatial specificity of MEG is not sufficient to separate proprioceptive finger representations of the same hand adequately or that their representations are overlapping.

neuroscience↗

bioRxiv2020

Processing of a spoken narrative in the human brain is shaped by family cultural background

Using neuroimaging, we studied influence of family cultural background on processing of an audiobook in human brain. The audiobook depicted life of two young Finnish men, one with the Finnish and the other with the Russian family background. Shared family cultural background enhanced similarity of narrative processing in the brain at prelexical, word, sentence, and narrative levels. Similarity was also enhanced in brain areas supporting imagery. The cultural background was further reflected as semantic differences in word lists by which the subjects described what had been on their minds when they heard the audiobook during neuroimaging. Strength of social identity shaped word, sentence, and narrative level processing in the brain. These effects might enhance mutual understanding between persons who share family cultural background and social identity and, conversely, deteriorate between-group mutual understanding in modern multicultural societies wherein native speakers of a language may assume highly similar understanding.

neuroscience↗