Search results for "aivotutkimus"
showing 10 items of 41 documents
Detecting differences with magnetoencephalography of somatosensory processing after tactile and electrical stimuli.
2018
Abstract Background Deviant stimuli within a standard, frequent stimulus train induce a cortical somatosensory mismatch response (SMMR). The SMMR reflects the brain’s automatic mechanism for the detection of change in a somatosensory domain. It is usually elicited by electrical stimulation, which activates nerve fibers and receptors in superficial and deep skin layers, whereas tactile stimulation is closer to natural stimulation and activates uniform fiber types. We recorded SMMRs after electrical and tactile stimuli. Method 306-channel magnetoencephalography recordings were made with 16 healthy adults under two conditions: electrical (eSMMR) and tactile (tSMMR) stimulations. The SMMR proto…
Transient seizure onset network for localization of epileptogenic zone: effective connectivity and graph theory-based analyses of ECoG data in tempor…
2018
Objective: Abnormal and dynamic epileptogenic networks cause difficulties for clinical epileptologists in the localization of the seizure onset zone (SOZ) and the epileptogenic zone (EZ) in preoperative assessments of patients with refractory epilepsy. The aim of this study is to investigate the characteristics of time-varying effective connectivity networks in various non-seizure and seizure periods, and to propose a quantitative approach for accurate localization of SOZ and EZ. Methods: We used electrocorticogram recordings in the temporal lobe and hippocampus from seven patients with temporal lobe epilepsy to characterize the effective connectivity dynamics at a high temporal resolution …
Social exclusion influences conditioned fear acquisition and generalization: A mediating effect from the medial prefrontal cortex
2020
Abstract Fear acquisition and generalization play key roles in promoting the survival of mammals and contribute to anxiety disorders. While previous research has provided much evidence for the repercussions of social exclusion on mental health, how social exclusion affects fear acquisition and generalization has received scant attention. In our study, participants were divided into two groups according to two Cyberball paradigm conditions (exclusion/inclusion). Both groups underwent a Pavlovian conditioning paradigm, functional near-infrared spectroscopy (fNIRS), and skin conductance response (SCR) assessments. We aimed to determine the effects of social exclusion on fear acquisition and ge…
Discovering dynamic task-modulated functional networks with specific spectral modes using MEG.
2019
Efficient neuronal communication between brain regions through oscillatory synchronization at certain frequencies is necessary for cognition. Such synchronized networks are transient and dynamic, established on the timescale of milliseconds in order to support ongoing cognitive operations. However, few studies characterizing dynamic electrophysiological brain networks have simultaneously accounted for temporal non-stationarity, spectral structure, and spatial properties. Here, we propose an analysis framework for characterizing the large-scale phase-coupling network dynamics during task performance using magnetoencephalography (MEG). We exploit the high spatiotemporal resolution of MEG to m…
Passive exposure to speech sounds modifies change detection brain responses in adults
2019
In early life auditory discrimination ability can be enhanced by passive sound exposure. In contrast, in adulthood passive exposure seems to be insufficient to promote discrimination ability, but this has been tested only with a single short exposure session in humans. We tested whether passive exposure to unfamiliar auditory stimuli can result in enhanced cortical discrimination ability and change detection in adult humans, and whether the possible learning effect generalizes to different stimuli. To address these issues, we exposed adult Finnish participants to Chinese lexical tones passively for 2 h per day on 4 consecutive days. Behavioral responses and the brain's event-related potenti…
Prior Precision Modulates the Minimization of Auditory Prediction Error
2019
International audience; The predictive coding model of perception proposes that successful representation of the perceptual world depends upon canceling out the discrepancy between prediction and sensory input (i.e., prediction error). Recent studies further suggest a distinction to be made between prediction error triggered by non-predicted stimuli of different prior precision (i.e., inverse variance). However, it is not fully understood how prediction error with different precision levels is minimized in the predictive process. Here, we conducted a magnetoencephalography (MEG) experiment which orthogonally manipulated prime-probe relation (for contextual precision) and stimulus repetition…
Discovering hidden brain network responses to naturalistic stimuli via tensor component analysis of multi-subject fMRI data
2021
The study of brain network interactions during naturalistic stimuli facilitates a deeper understanding of human brain function. To estimate large-scale brain networks evoked with naturalistic stimuli, a tensor component analysis (TCA) based framework was used to characterize shared spatio-temporal patterns across subjects in a purely data-driven manner. In this framework, a third-order tensor is constructed from the timeseries extracted from all brain regions from a given parcellation, for all participants, with modes of the tensor corresponding to spatial distribution, time series and participants. TCA then reveals spatially and temporally shared components, i.e., evoked networks with the …
Dynamic Community Detection for Brain Functional Networks during Music Listening with Block Component Analysis
2023
Publisher Copyright: Author The human brain can be described as a complex network of functional connections between distinct regions, referred to as the brain functional network. Recent studies show that the functional network is a dynamic process and its community structure evolves with time during continuous task performance. Consequently, it is important for the understanding of the human brain to develop dynamic community detection techniques for such time-varying functional networks. Here, we propose a temporal clustering framework based on a set of network generative models and surprisingly it can be linked to Block Component Analysis to detect and track the latent community structure…
Multi-modality of polysomnography signals’ fusion for automatic sleep scoring
2019
Abstract Objective The study aims to develop an automatic sleep scoring method by fusing different polysomnography (PSG) signals and further to investigate PSG signals’ contribution to the scoring result. Methods Eight combinations of four modalities of PSG signals, namely electroencephalogram (EEG), electrooculogram (EOG), electromyogram (EMG), and electrocardiogram (ECG) were considered to find the optimal fusion of PSG signals. A total of 232 features, covering statistical characters, frequency characters, time-frequency characters, fractal characters, entropy characters and nonlinear characters, were derived from these PSG signals. To select the optimal features for each signal fusion, …
Exploring Frequency-Dependent Brain Networks from Ongoing EEG Using Spatial ICA During Music Listening
2020
Recently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during freely listening to music. We used a data-driven method that co…