Irina Simanova

Identifying object categories from event-related EEG: toward decoding of conceptual representations

Multivariate pattern analysis is a technique that allows the decoding of conceptual information such as the semantic category of a perceived object from neuroimaging data. Impressive single-trial classification results have been reported in studies that used fMRI. Here, we investigate the possibility to identify conceptual representations from event-related EEG based on the presentation of an object in different modalities: its spoken name, its visual representation and its written name. We used Bayesian logistic regression with a multivariate Laplace prior for classification. Marked differences in classification performance were observed for the tested modalities. Highest accuracies (89% correctly classified trials) were attained when classifying object drawings. In auditory and orthographical modalities, results were lower though still significant for some subjects. The employed classification method allowed for a precise temporal localization of the features that contributed to the performance of the classifier for three modalities. These findings could help to further understand the mechanisms underlying conceptual representations. The study also provides a first step towards the use of concept decoding in the context of real-time brain-computer interface applications.

Mapping of functional brain activity in freely behaving rats during voluntary running using manganese-enhanced MRI: Implication for longitudinal studies

Magnetic resonance imaging (MRI) is widely used in basic and clinical research to map the structural and functional organization of the brain. An important need of MR research is for contrast agents that improve soft-tissue contrast, enable visualization of neuronal tracks, and enhance the capacity of MRI to provide functional information at different temporal scales. Unchelated manganese can be such an agent, and manganese-enhanced MRI (MEMRI) can potentially be an excellent technique for localization of brain activity (for review see Silva et al., 2004). Yet, the toxicity of manganese presents a major limitation for employing MEMRI in behavioral paradigms. We have tested systematically the voluntary wheel running behavior of rats after systemic application of MnCl(2) in a dose range of 16-80 mg/kg, which is commonly used in MEMRI studies. The results show a robust dose-dependent decrease in motor performance, which was accompanied by weight loss and decrease in food intake. The adverse effects lasted for up to 7 post-injection days. The lowest dose of MnCl(2) (16 mg/kg) produced minimal adverse effects, but was not sufficient for functional mapping. We have therefore evaluated an alternative method of manganese delivery via osmotic pumps, which provide a continuous and slow release of manganese. In contrast to a single systemic injection, the pump method did not produce any adverse locomotor effects, while achieving a cumulative concentration of manganese (80 mg/kg) sufficient for functional mapping. Thus, MEMRI with such an optimized manganese delivery that avoids toxic effects can be safely applied for longitudinal studies in behaving animals.

Modality-Independent Decoding of Semantic Information from the Human Brain

An ability to decode semantic information from fMRI spatial patterns has been demonstrated in previous studies mostly for 1 specific input modality. In this study, we aimed to decode semantic category independent of the modality in which an object was presented. Using a searchlight method, we were able to predict the stimulus category from the data while participants performed a semantic categorization task with 4 stimulus modalities (spoken and written names, photographs, and natural sounds). Significant classification performance was achieved in all 4 modalities. Modality-independent decoding was implemented by training and testing the searchlight method across modalities. This allowed the localization of those brain regions, which correctly discriminated between the categories, independent of stimulus modality. The analysis revealed large clusters of voxels in the left inferior temporal cortex and in frontal regions. These voxels also allowed category discrimination in a free recall session where subjects recalled the objects in the absence of external stimuli. The results show that semantic information can be decoded from the fMRI signal independently of the input modality and have clear implications for understanding the functional mechanisms of semantic memory.

Behavioral, electrophysiological and histopathological consequences of systemic manganese administration in MEMRI.

Manganese (Mn(2+))-enhanced magnetic resonance imaging (MEMRI) offers the possibility to generate longitudinal maps of brain activity in unrestrained and behaving animals. However, Mn(2+) is a metabolic toxin and a competitive inhibitor for Ca(2+), and therefore, a yet unsolved question in MEMRI studies is whether the concentrations of metal ion used may alter brain physiology. In the present work we have investigated the behavioral, electrophysiological and histopathological consequences of MnCl(2) administration at concentrations and dosage protocols regularly used in MEMRI. Three groups of animals were sc injected with saline, 0.1 and 0.5 mmol/kg MnCl(2), respectively. In vivo electrophysiological recordings in the hippocampal formation revealed a mild but detectable decrease in both excitatory postsynaptic potentials (EPSP) and population spike (PS) amplitude under the highest MnCl(2) dose. The EPSP to PS ratio was preserved at control levels, indicating that neuronal excitability was not affected. Experiments of pair pulse facilitation demonstrated a dose dependent increase in the potentiation of the second pulse, suggesting presynaptic Ca(2+) competition as the mechanism for the decreased neuronal response. Tetanization of the perforant path induced a long-term potentiation of synaptic transmission that was comparable in all groups, regardless of treatment. Accordingly, the choice accuracy tested on a hippocampal-dependent learning task was not affected. However, the response latency in the same task was largely increased in the group receiving 0.5 mmol/kg of MnCl(2). Immunohistological examination of the hippocampus at the end of the experiments revealed no sign of neuronal toxicity or glial reaction. Although we show that MEMRI at 0.1 mmol/Kg MnCl(2) may be safely applied to the study of cognitive networks, a detailed assessment of toxicity is strongly recommended for each particular study and Mn(2+) administration protocol.

Linguistic priors shape categorical perception

ABSTRACT This article reviews recent literature on the role of top-down feedback processes in semantic representations in the brain. Empirical studies on perception and theoretical models of semantic cognition show that sensory input is filtered and interpreted based on predictions from higher order cognitive areas. Here, we review the present evidence to the proposal that linguistic constructs, in particular, words, could serve as effective priors, facilitating perception and integration of sensory information. We address a number of theoretical questions arising from this assumption. The focus here is if linguistic categories have a direct top-down effect on early stages of perception; or rather interact with later processing stages such as semantic analysis. We discuss experimental approaches that could discriminate between these possibilities. Taken together, this article provides a review on the interaction between language and perception from the predictive perspective, and suggests avenues to investigate the underlying mechanisms from this perspective.

Predicting the semantic category of internally generated words from neuromagnetic recordings

In this study, we explore the possibility to predict the semantic category of words from brain signals in a free word generation task. Participants produced single words from different semantic categories in a modified semantic fluency task. A Bayesian logistic regression classifier was trained to predict the semantic category of words from single-trial MEG data. Significant classification accuracies were achieved using sensor-level MEG time series at the time interval of conceptual preparation. Semantic category prediction was also possible using source-reconstructed time series, based on minimum norm estimates of cortical activity. Brain regions that contributed most to classification on the source level were identified. These were the left inferior frontal gyrus, left middle frontal gyrus, and left posterior middle temporal gyrus. Additionally, the temporal dynamics of brain activity underlying the semantic preparation during word generation was explored. These results provide important insights about central aspects of language production.

Communicative intent modulates production and comprehension of actions and gestures: A Kinect study

Actions may be used to directly act on the world around us, or as a means of communication. Effective communication requires the addressee to recognize the act as being communicative. Humans are sensitive to ostensive communicative cues, such as direct eye gaze (Csibra & Gergely, 2009). However, there may be additional cues present in the action or gesture itself. Here we investigate features that characterize the initiation of a communicative interaction in both production and comprehension. We asked 40 participants to perform 31 pairs of object-directed actions and representational gestures in more- or less- communicative contexts. Data were collected using motion capture technology for kinematics and video recording for eye-gaze. With these data, we focused on two issues. First, if and how actions and gestures are systematically modulated when performed in a communicative context. Second, if observers exploit such kinematic information to classify an act as communicative. Our study showed that during production the communicative context modulates space-time dimensions of kinematics and elicits an increase in addressee-directed eye-gaze. Naïve participants detected communicative intent in actions and gestures preferentially using eye-gaze information, only utilizing kinematic information when eye-gaze was unavailable. Our study highlights the general communicative modulation of action and gesture kinematics during production but also shows that addressees only exploit this modulation to recognize communicative intention in the absence of eye-gaze. We discuss these findings in terms of distinctive but potentially overlapping functions of addressee directed eye-gaze and kinematic modulations within the wider context of human communication and learning.

Toward the markerless and automatic analysis of kinematic features: A toolkit for gesture and movement research

Action, gesture, and sign represent unique aspects of human communication that use form and movement to convey meaning. Researchers typically use manual coding of video data to characterize naturalistic, meaningful movements at various levels of description, but the availability of markerless motion-tracking technology allows for quantification of the kinematic features of gestures or any meaningful human movement. We present a novel protocol for extracting a set of kinematic features from movements recorded with Microsoft Kinect. Our protocol captures spatial and temporal features, such as height, velocity, submovements/strokes, and holds. This approach is based on studies of communicative actions and gestures and attempts to capture features that are consistently implicated as important kinematic aspects of communication. We provide open-source code for the protocol, a description of how the features are calculated, a validation of these features as quantified by our protocol versus manual coders, and a discussion of how the protocol can be applied. The protocol effectively quantifies kinematic features that are important in the production (e.g., characterizing different contexts) as well as the comprehension (e.g., used by addressees to understand intent and semantics) of manual acts. The protocol can also be integrated with qualitative analysis, allowing fast and objective demarcation of movement units, providing accurate coding even of complex movements. This can be useful to clinicians, as well as to researchers studying multimodal communication or human–robot interactions. By making this protocol available, we hope to provide a tool that can be applied to understanding meaningful movement characteristics in human communication.