The role of right and left parietal lobes in the conceptual processing of numbers

Neuropsychological and functional imaging studies have associated the conceptual processing of numbers with bilateral parietal regions (including intraparietal sulcus). However, the processes driving these effects remain unclear because both left and right posterior parietal regions are activated by many other conceptual, perceptual, attention, and response-selection processes. To dissociate parietal activation that is number-selective from parietal activation related to other stimulus or response-selection processes, we used fMRI to compare numbers and object names during exactly the same conceptual and perceptual tasks while factoring out activations correlating with response times. We found that right parietal activation was higher for conceptual decisions on numbers relative to the same tasks on object names, even when response time effects were fully factored out. In contrast, left parietal activation for numbers was equally involved in conceptual processing of object names. We suggest that left parietal activation for numbers reflects a range of processes, including the retrieval of learnt facts that are also involved in conceptual decisions on object names. In contrast, number selectivity in right parietal cortex reflects processes that are more involved in conceptual decisions on numbers than object names. Our results generate a new set of hypotheses that have implications for the design of future behavioral and functional imaging studies of patients with left and right parietal damage

Neural overlap of L1 and L2 semantic representations across visual and auditory modalities : a decoding approach/

This study investigated whether brain activity in Dutch-French bilinguals during semantic access to concepts from one language could be used to predict neural activation during access to the same concepts from another language, in different language modalities/tasks. This was tested using multi-voxel pattern analysis (MVPA), within and across language comprehension (word listening and word reading) and production (picture naming). It was possible to identify the picture or word named, read or heard in one language (e.g. maan, meaning moon) based on the brain activity in a distributed bilateral brain network while, respectively, naming, reading or listening to the picture or word in the other language (e.g. lune). The brain regions identified differed across tasks. During picture naming, brain activation in the occipital and temporal regions allowed concepts to be predicted across languages. During word listening and word reading, across-language predictions were observed in the rolandic operculum and several motor-related areas (pre- and postcentral, the cerebellum). In addition, across-language predictions during reading were identified in regions typically associated with semantic processing (left inferior frontal, middle temporal cortex, right cerebellum and precuneus) and visual processing (inferior and middle occipital regions and calcarine sulcus). Furthermore, across modalities and languages, the left lingual gyrus showed semantic overlap across production and word reading. These findings support the idea of at least partially language- and modality-independent semantic neural representations

A tutorial on group effective connectivity analysis, part 2: second level analysis with PEB

This tutorial provides a worked example of using Dynamic Causal Modelling (DCM) and Parametric Empirical Bayes (PEB) to characterise inter-subject variability in neural circuitry (effective connectivity). This involves specifying a hierarchical model with two or more levels. At the first level, state space models (DCMs) are used to infer the effective connectivity that best explains a subject's neuroimaging timeseries (e.g. fMRI, MEG, EEG). Subject-specific connectivity parameters are then taken to the group level, where they are modelled using a General Linear Model (GLM) that partitions between-subject variability into designed effects and additive random effects. The ensuing (Bayesian) hierarchical model conveys both the estimated connection strengths and their uncertainty (i.e., posterior covariance) from the subject to the group level; enabling hypotheses to be tested about the commonalities and differences across subjects. This approach can also finesse parameter estimation at the subject level, by using the group-level parameters as empirical priors. We walk through this approach in detail, using data from a published fMRI experiment that characterised individual differences in hemispheric lateralization in a semantic processing task. The preliminary subject specific DCM analysis is covered in detail in a companion paper. This tutorial is accompanied by the example dataset and step-by-step instructions to reproduce the analyses

A Generative Model of Speech Production in Broca’s and Wernicke’s Areas

Speech production involves the generation of an auditory signal from the articulators and vocal tract. When the intended auditory signal does not match the produced sounds, subsequent articulatory commands can be adjusted to reduce the difference between the intended and produced sounds. This requires an internal model of the intended speech output that can be compared to the produced speech. The aim of this functional imaging study was to identify brain activation related to the internal model of speech production after activation related to vocalization, auditory feedback, and movement in the articulators had been controlled. There were four conditions: silent articulation of speech, non-speech mouth movements, finger tapping, and visual fixation. In the speech conditions, participants produced the mouth movements associated with the words “one” and “three.” We eliminated auditory feedback from the spoken output by instructing participants to articulate these words without producing any sound. The non-speech mouth movement conditions involved lip pursing and tongue protrusions to control for movement in the articulators. The main difference between our speech and non-speech mouth movement conditions is that prior experience producing speech sounds leads to the automatic and covert generation of auditory and phonological associations that may play a role in predicting auditory feedback. We found that, relative to non-speech mouth movements, silent speech activated Broca’s area in the left dorsal pars opercularis and Wernicke’s area in the left posterior superior temporal sulcus. We discuss these results in the context of a generative model of speech production and propose that Broca’s and Wernicke’s areas may be involved in predicting the speech output that follows articulation. These predictions could provide a mechanism by which rapid movement of the articulators is precisely matched to the intended speech outputs during future articulations

Where Bottom-up Meets Top-down: Neuronal Interactions during Perception and Imagery

Functional magnetic resonance imaging (fMRI) studies have identified category-selective regions in ventral occipito-temporal cortex that respond preferentially to faces and other objects. The extent to which these patterns of activation are modulated by bottom-up or top-down mechanisms is currently unknown. We combined fMRI and dynamic causal modelling to investigate neuronal interactions between occipito-temporal, parietal and frontal regions, during visual perception and visual imagery of faces, houses and chairs. Our results indicate that, during visual perception, category-selective patterns of activation in extrastriate cortex are mediated by content-sensitive forward connections from early visual areas. In contrast, during visual imagery, category-selective activation is mediated by content-sensitive backward connections from prefrontal cortex. Additionally, we report content-unrelated connectivity between parietal cortex and the category-selective regions, during both perception and imagery. Thus, our investigation revealed that neuronal interactions between occipito-temporal, parietal and frontal regions are task- and stimulus-dependent. Sensory representations of faces and objects are mediated by bottom-up mechanisms arising in early visual areas and top-down mechanisms arising in prefrontal cortex, during perception and imagery respectively. Additionally non-selective, top-down processes, originating in superior parietal areas, contribute to the generation of mental images, regardless of their content, and their maintenance in the ‘mind's eye

MODELING FISH LENGTH DISTRIBUTION USING A MIXTURE TECHNIQUE

In fisheries science, length and age are important aspects of fish life history. Length is a function of growth, which provides an integrated measure of the environmental and endogenous conditions, e.g. genetics, affecting individuals and populations. Length at age data can be used to assess quality and quantity of habitat, food availability, or the need for and influence of management activities. Statistical mixture techniques may be used as a means to effectively model fish length distribution. A three-component mixture model, based on normal variates, was employed to describe length distribution in mountain whitefish species. The resulting model provided parameter estimates with meaningful biological interpretations, which were in turn used for inferential and comparative purposes. The technique will be demonstrated with reference to seven years of bio-monitoring data collected from the Kootenai River in Northern Idaho prior to and post nutrient addition treatment

Modules and brain mapping

This review highlights the key role of modularity and the additive factors method in functional neuroimaging. Our focus is on structure–function mappings in the human brain and how these are disclosed by brain mapping. We describe how modularity of processing (and possibly processes) was a key point of reference for establishing functional segregation as a principle of brain organization. Furthermore, modularity plays a crucial role when trying to characterize distributed brain responses in terms of functional integration or coupling among brain areas. We consider additive factors logic and how it helped to shape the design and interpretation of studies at the inception of brain mapping, with a special focus on factorial designs. We look at factorial designs in activation experiments and in the context of lesion–deficit mapping. In both cases, the presence or absence of interactions among various experimental factors has proven essential in understanding the context-sensitive nature of distributed but modular processing and discerning the nature of (potentially degenerate) structure–function relationships in cognitive neuroscience

Neuronal activation for semantically reversible sentences

Semantically reversible sentences are prone to misinterpretation and take longer for typically developing children and adults to comprehend; they are also particularly problematic for those with language difficulties such as aphasia or Specific Language Impairment. In our study, we used fMRI to compare the processing of semantically reversible and nonreversible sentences in 41 healthy participants to identify how semantic reversibility influences neuronal activation. By including several linguistic and nonlinguistic conditions within our paradigm, we were also able to test whether the processing of semantically reversible sentences places additional load on sentence-specific processing, such as syntactic processing and syntactic-semantic integration, or on phonological working memory. Our results identified increased activation for reversible sentences in a region on the left temporal–parietal boundary, which was also activated when the same group of participants carried out an articulation task which involved saying “one, three” repeatedly. We conclude that the processing of semantically reversible sentences places additional demands on the subarticulation component of phonological working memory