Biology subjects

Ahveninen, J.

Publications and source records attributed to Ahveninen, J..

17 recordsLinked to original sources

bioRxiv2026

Relating layer fMRI signals to acoustics and intracranial neuronal activity in the human auditory cortex in a naturalistic design

Naturalistic auditory perception engages feedforward and feedback dynamics across cortical depths, yet how these are organized in the human auditory cortex has been difficult to verify noninvasively. Here, we examine depth-dependent coupling between neuronal activity and fMRI during passive music listening. Depth-specific fMRI responses were modeled using neuronal oscillation envelopes elicited by the same naturalistic stimuli from a separate group of patients under intracranial EEG monitoring. From deep toward superficial depths, the relationship between oscillatory power and fMRI responses systematically changed: alpha/beta activity (8-30 Hz) was increasingly associated with negative fMRI responses, mapping top-down feedback, while gamma band (>30 Hz) oscillations showed increasingly positive associations. Relative to a purely acoustical fMRI baseline, broadband high-frequency activity (>70 Hz), a proxy for neuronal firing, showed the strongest coupling to BOLD signals at intermediate cortical depths receiving feedforward inputs from earlier auditory pathways. Our findings reveal a spectrolaminar organization of neurovascular coupling in the human auditory cortex.

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bioRxiv2025

Fast voxel and structural MRI realignment to mitigate inter-acquisition motion for spectroscopy

Magnetic resonance spectroscopy (MRS) non-invasively measures the biochemical composition within a predefined brain region, enabling quantification of neurochemicals with biological and clinical relevance, such as N-acetylaspartate, creatine, choline, glutamate, and gamma-aminobutyric acid. However, accurate MRS quantification is compromised by subject motion displacing the prescribed location, a common problem during long scans or with motion-prone populations such as children and patients. Furthermore, displacement into bone tissue contaminates MRS data with noisy artifacts, often rendering them unusable. While promising solutions exist to address motion-related issues, many rely on specialized infrastructure and expertise available only at a limited number of research centers. We propose a fast and straightforward method that acquires a head scout (18 s) MRI sequence following potential motion, automatically repositions the prescribed voxel with the scanners built-in AutoAlign function, and realigns the T1-weighted image to the updated position for anatomical segmentation. Using voxels prescribed in the prefrontal cortex, thalamus, and left superior temporal gyrus, we demonstrated that this realignment method successfully restored displaced voxels to their intended locations, eliminating bone contamination while improving voxel targeting through greater overlap with intended regions and more consistent voxel placement across subjects. This solution offers a quick and practical way for correcting subject motion between scans by combining available tools that are readily accessible even to new users, while more sophisticated motion correction technologies continue to develop towards broader adoption.

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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.

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bioRxiv2024

Decoding auditory working memory content from EEG aftereffects of auditory-cortical TMS

Working memory (WM), short term maintenance of information for goal directed behavior, is essential to human cognition. Identifying the neural mechanisms supporting WM is a focal point of neuroscientific research. One prominent theory hypothesizes that WM content is carried in "activity-silent" brain states involving short-term synaptic changes. Information carried in such brain states could be decodable from content-specific changes in responses to unrelated "impulse stimuli". Here, we used single-pulse transcranial magnetic stimulation (spTMS) as the impulse stimulus and then decoded content maintained in WM from EEG using multivariate pattern analysis (MVPA) with robust non-parametric permutation testing. The decoding accuracy of WM content significantly enhanced after spTMS was delivered to the posterior superior temporal cortex during WM maintenance. Our results show that WM maintenance involves brain states, which are activity silent relative to other intrinsic processes visible in the EEG signal.

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bioRxiv2024

Characterizing directional dynamics of semantic prediction based on inter-regional temporal generalization

The event-related potential/field component N400(m) has been widely used as a neural index for semantic prediction. It has long been hypothesized that feedback information from inferior frontal areas plays a critical role in generating the N400. However, due to limitations in causal connectivity estimation, direct testing of this hypothesis has remained difficult. Here, magnetoencephalography (MEG) data was obtained during a classic N400 paradigm where the semantic predictability of a fixed target noun was manipulated in simple German sentences. To estimate causality, we implemented a novel approach based on machine learning and temporal generalization to estimate the effect of inferior frontal gyrus (IFG) on temporal areas. In this method, a support vector machine (SVM) classifier is trained on each time point of the neural activity in IFG to classify less predicted (LP) and highly predicted (HP) nouns and then tested on all time points of superior/middle temporal sub- regions activity (and vice versa, to establish spatio-temporal evidence for or against causality). The decoding accuracy was significantly above chance level when the classifier was trained on IFG activity and tested on future activity in superior and middle temporal gyrus (STG/MTG). The results present new evidence for a model predictive speech comprehension where predictive IFG activity is fed back to shape subsequent activity in STG/MTG, implying a feedback mechanism in N400 generation. In combination with the also observed strong feedforward effect from left STG/MTG to IFG, our findings provide evidence of dynamic feedback and feedforward influences between IFG and temporal areas during N400 generation.

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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.

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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.

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bioRxiv2023

Decoding auditory working memory content from intracranial high frequency activity in humans

Working memory (WM), the human brains system for maintaining and manipulating information over short timescales, is critical for goal-directed behavior. Classic neurophysiological models, which emphasize persistent delay activity, are being challenged by an idea that WM is maintained through dynamic and activity-silent mechanisms, where the memory trace is preserved by transient changes in the connections between neurons. To date, human evidence for this alternative model has been limited to non-invasive studies. Here, leveraging high-resolution intracranial stereo-EEG with advanced machine learning decoding techniques, we investigate neuronal mechanisms of human auditory WM. Neuronal activity is quantified as broadband high frequency activity (70-190 Hz), a correlate of neuronal firing activity. Our multivariate pattern analyses, validated via robust non-parametric permutation testing, show that WM content is represented in multiple brain regions, exhibiting dynamic rather than persistent delay activity. Crucially, by using task-irrelevant sounds to probe latent mnemonic states, we provide the first human intracranial evidence of activity silent WM maintenance in a local sensory network.

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bioRxiv2023

Auditory aspects of multisensory working memory are retrieved better than visual aspects

Working memory (WM) reflects the transient maintenance of information in the absence of external input, which can be attained via multiple senses separately or simultaneously. Pertaining to WM, the prevailing literature suggests the dominance of vision over other sensory systems. However, this imbalance may be stemming from challenges in finding comparable stimuli across modalities. Here, we addressed this problem by using a balanced multisensory retro-cue WM design, which employed combinations of auditory (ripple sounds) and visuospatial (Gabor patches) patterns, adjusted relative to each participants discrimination ability. In three separate experiments, the participant was asked to determine whether the (retro-cued) auditory and/or visual items maintained in WM matched or mismatched the subsequent probe stimulus. In Experiment 1, all stimuli were audiovisual, and the probes were either fully mismatching, only partially mismatching, or fully matching the memorized item. Experiment 2 was otherwise same as Experiment 1, but the probes were unimodal. In Experiment 3, the participant was cued to maintain only the auditory or visual aspect of an audiovisual item pair. In two of the three experiments, the participant matching performance was significantly more accurate for the auditory than visual attributes of probes. When the perceptual and task demands are bimodally equated, auditory attributes can be matched to multisensory items in WM at least as accurately as, if not more precisely than, their visual counterparts.

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bioRxiv2023

Role of Articulatory Motor Networks in Perceptual Categorization of Speech Signals: A 7 T fMRI Study

BACKGROUNDThe association between brain regions involved in speech production and those that play a role in speech perception is not yet fully understood. We compared speech production related brain activity with activations resulting from perceptual categorization of syllables using high field 7 Tesla functional magnetic resonance imaging (fMRI) at 1-mm isotropic voxel resolution, enabling high localization accuracy compared to previous studies. METHODSBlood oxygenation level dependent (BOLD) signals were obtained in 20 normal hearing subjects using a simultaneous multi-slice (SMS) 7T echo-planar imaging (EPI) acquisition with whole-head coverage and 1 mm isotropic resolution. In a speech production localizer task, subjects were asked to produce a silent lip-round vowel /u/ in response to the visual cue "U" or purse their lips when they saw the cue "P". In a phoneme discrimination task, subjects were presented with pairs of syllables, which were equiprobably identical or different along an 8-step continuum between the prototypic /ba/ and /da/ sounds. After the presentation of each stimulus pair, the subjects were asked to indicate whether the two syllables they heard were identical or different by pressing one of two buttons. In a phoneme classification task, the subjects heard only one syllable and asked to indicate whether it was /ba/ or /da/. RESULTSUnivariate fMRI analyses using a parametric modulation approach suggested that left motor, premotor, and frontal cortex BOLD activations correlate with phoneme category variability in the /ba/-/da/ discrimination task. In contrast, the variability related to acoustic features of the phonemes were the highest in the right primary auditory cortex. Our multivariate pattern analysis (MVPA) suggested that left precentral/inferior frontal cortex areas, which were associated with speech production according to the localizer task, play a role also in perceptual categorization of the syllables. CONCLUSIONSThe results support the hypothesis that articulatory motor networks in the left hemisphere that are activated during speech production could also have a role in perceptual categorization of syllables. Importantly, high voxel-resolution combined with advanced coil technology allowed us to pinpoint the exact brain regions involved in both perception and production tasks.

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bioRxiv2023

Neuronal modeling of magnetoencephalography responses in auditory cortex to auditory and visual stimuli

Previous studies have demonstrated that auditory cortex activity can be influenced by crosssensory visual inputs. Intracortical recordings in non-human primates (NHP) have suggested a bottom-up feedforward (FF) type laminar profile for auditory evoked but top-down feedback (FB) type for cross-sensory visual evoked activity in the auditory cortex. To test whether this principle applies also to humans, we analyzed magnetoencephalography (MEG) responses from eight human subjects (six females) evoked by simple auditory or visual stimuli. In the estimated MEG source waveforms for auditory cortex region of interest, auditory evoked responses showed peaks at 37 and 90 ms and cross-sensory visual responses at 125 ms. The inputs to the auditory cortex were then modeled through FF and FB type connections targeting different cortical layers using the Human Neocortical Neurosolver (HNN), which consists of a neocortical circuit model linking the cellular- and circuit-level mechanisms to MEG. The HNN models suggested that the measured auditory response could be explained by an FF input followed by an FB input, and the crosssensory visual response by an FB input. Thus, the combined MEG and HNN results support the hypothesis that cross-sensory visual input in the auditory cortex is of FB type. The results also illustrate how the dynamic patterns of the estimated MEG/EEG source activity can provide information about the characteristics of the input into a cortical area in terms of the hierarchical organization among areas. Significance statementLaminar intracortical profiles of activity characterize feedforward- and feedback-type influences in the inputs to a cortical area. By combining magnetoencephalography (MEG) and biophysical computational neural modeling, we obtained evidence of cross-sensory visual evoked activity in human auditory cortex being of feedback type. The finding is consistent with previous intracortical recordings in non-human primates. The results illustrate how patterns of MEG source activity can be interpreted in the context of the hierarchical organization among cortical areas.

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bioRxiv2022

Visual stimuli modulate local field potentials but drive no high-frequency activity in human auditory cortex

Neuroimaging studies suggest cross-sensory visual influences in human auditory cortices. Whether these influences reflect active visual processing in human auditory cortices (ACs), which drives neuronal firing and concurrent broadband high-frequency activity (BHFA; >70 Hz), or whether they merely modulate sound processing is still debatable. Here, we presented auditory, visual, and audiovisual stimuli to 16 participants (7 women, 9 men) with stereo-EEG depth electrodes implanted near ACs for presurgical monitoring. Anatomically normalized group analyses were facilitated by inverse modeling of intracranial source currents. Analyses of intracranial event-related potentials (iERP) suggested cross-sensory responses to visual stimuli in ACs, which lagged the earliest auditory responses by several tens of milliseconds. Visual stimuli also modulated the phase of intrinsic low-frequency oscillations and triggered 15-30-Hz event-related desynchronization in ACs. However, BHFA, a putative correlate of neuronal firing, was not significantly increased in ACs after visual stimuli, not even when they coincided with auditory stimuli. Intracranial recordings demonstrate cross-sensory modulations, but no indication of active visual processing in human ACs. Significance StatementVisual information has a profound influence on auditory processing, particularly in noisy conditions. These "cross-sensory" influences start already in auditory cortices, the brain area that processes sound signals. It has, however, been unclear whether auditory cortex actively processes visual information or whether visual signals only change the way sounds are processed. We studied this question by neurophysiological recordings from 16 participants with epilepsy who had electrodes implanted in their brains due to medical reasons. Using these intracranial recordings, we show that cross-sensory visual information modulates sound processing but triggers no high-frequency activity -- a correlate of local neuronal firing -- in auditory cortex. This result provides important information on the role of sensory areas in multisensory processing in the human brain.

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bioRxiv2020

Distributed source modeling of intracranial stereoelectroencephalographic measurements

Intracranial stereoelectroencephalography (sEEG) provides unsurpassed sensitivity and specificity for human neurophysiology. However, sEEG group analyses are complicated because the electrode implantations differ greatly across individuals. Here, using an auditory experiment as the test case, we developed a distributed, anatomically realistic sEEG source-modeling approach for within- and between-subject analyses. In addition to intracranial event-related potentials (iERP), we also estimated the sources of high broadband gamma activity (HBBG), a putative correlate of local neural firing. The source models accounted for a significant portion of the variance of the sEEG measurements in leave-one-out cross-validation. After logarithmic transformations, the sensitivity and signal-to-noise ratio were linearly inversely related to the minimal distance between the brain location and electrode contacts (slope{approx}-3.6). The HGGB source estimates were remarkably consistent with analyses of intracranial-contact data. In conclusion, distributed sEEG source modeling provides a powerful neuroimaging tool, which facilitates anatomically-normalized group analyses of both iERP and HBBG.

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bioRxiv2020

Individual variability in functional organization of the human and monkey auditory cortex

Accumulating evidence shows that auditory cortex (AC) of humans, and other primates, is involved in more complex cognitive processes than feature segregation only, which are shaped by experience-dependent plasticity and thus likely show substantial individual variability. However, thus far, individual variability of ACs has been considered a methodological impediment rather than a phenomenon of theoretical importance. Here, we examined the variability of ACs using intrinsic functional connectivity patterns in humans and macaques. Our results demonstrate that in humans, functional variability is 1) greater near the non-primary than primary ACs, 2) greater in ACs than comparable visual areas, and 3) greater in the left than right ACs. Remarkably similar modality differences and lateralization of variability were observed in macaques. These connectivity-based findings are consistent with a confirmatory task-based fMRI analysis. The quantitative proof of the exceptional variability of ACs has implications for understanding the evolution of advanced auditory functions in humans.

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bioRxiv2019

Cortical auditory distance representation based on direct-to-reverberant energy ratio

Auditory distance perception and its neuronal mechanisms are poorly understood, mainly because 1) it is difficult to separate distance processing from intensity processing, 2) multiple intensity-independent distance cues are often available, and 3) the cues are combined in a context-dependent way. A recent fMRI study identified human auditory cortical area representing intensity-independent distance for sources presented along the interaural axis (Kopco et al., PNAS, 109, 11019-11024). For these sources, two intensity-independent cues are available, interaural level difference (ILD) and direct-to-reverberant energy ratio (DRR). Thus, the observed activations may have been contributed by not only distance-related, but also direction-encoding neuron populations sensitive to ILD. Here, the paradigm from the previous study was used to examine DRR-based distance representation for sounds originating in front of the listener, where ILD is not available. In a virtual environment, we performed behavioral and fMRI experiments, combined with computational analyses to identify the neural representation of distance based on DRR. The stimuli varied in distance (15-100 cm) while their received intensity was varied randomly and independently of distance. Behavioral performance showed that intensity-independent distance discrimination is accurate for frontal stimuli, even though it is worse than for lateral stimuli. fMRI activations for sounds varying in frontal distance, as compared to varying only in intensity, increased bilaterally in the posterior banks of Heschl's gyri, the planum temporale, and posterior superior temporal gyrus regions. Taken together, these results suggest that posterior human auditory cortex areas contain neuron populations that are sensitive to distance independent of intensity and of binaural cues relevant for directional hearing.\n\nHighlightsO_LIPosterior auditory cortices (AC) are sensitive to frontally presented distance cues\nC_LIO_LIThese effects are independent of intensity- and direction-related binaural cues\nC_LIO_LIfMRI activations to frontal distance cues are found in the right and left AC\nC_LIO_LIThe frontal reverberation-related auditory distance cues are behaviorally relevant\nC_LI

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bioRxiv2019

Solving High-Resolution Forward Problems for Extra- and Intracranial Neurophysiological Recordings Using Boundary Element Fast Multipole Method

We present a general numerical approach for solving the forward problem in high-resolution. This approach can be employed in the analysis of noninvasive electroencephalography (EEG) and magnetoencephalography (MEG) as well as invasive electrocorticography (ECoG), stereoencephalography (sEEG), and local field potential (LFP) recordings. The underlying algorithm is our recently developed boundary element fast multipole method (BEM-FMM) that simulates anatomically realistic head models with unprecedented numerical accuracy and speed. This is achieved by utilizing the adjoint double layer formulation and zeroth-order basis functions in conjunction with the FMM acceleration. We present the mathematical formalism in detail and validate the method by applying it to the canonical multilayer sphere problem. The numerical error of BEM-FMM is 2-10 times lower while the computational speed is 1.5-20 times faster than those of the standard first-order FEM. We present four practical case studies: (i) evaluation of the effect of a detailed head model on the accuracy of EEG/MEG forward solution; (ii) demonstration of the ability to accurately calculate the electric potential and the magnetic field in the immediate vicinity of the sources and conductivity boundaries; (iii) computation of the field of a spatially extended cortical equivalent dipole layer; and (iv) taking into account the effect a fontanel for infant EEG source modeling and comparison of the results with a commercially available FEM. In all cases, BEM-FMM provided versatile, fast, and accurate high-resolution modeling of the electromagnetic field and has the potential of becoming a standard tool for modeling both extracranial and intracranial electrophysiological signals.

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bioRxiv2018

Cross-Modal Cue Effects in Motion Transparency Processing

The everyday environment brings about many competing inputs from different modalities to our sensory systems. The ability to filter these multisensory inputs in order to identify and efficiently utilize useful spatial cues is necessary to detect and process the relevant information. In the present study, we investigate how feature-based attention affects the detection of motion across sensory modalities. We were interested to determine how subjects use intramodal, crossmodal auditory, and combined audiovisual motion cues to attend to specific visual motion signals. The results show that in most cases, both visual and auditory cues enhance feature-based orienting to a visual motion pattern that is presented among distractor patterns. Furthermore, in many cases, detection of transparent motion patterns was significantly more accurate after combined visual-auditory than unimodal attention cues. Whereas previous studies have shown crossmodal effects of spatial attention, our results demonstrate a spread of crossmodal feature-based attention cues, which have been matched for the detection threshold of the visual target. These effects were evident in comparisons between cued and uncued conditions, as well as in analyses comparing the effects of valid vs. invalid cues.

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