Biology subjects

Weber, K.

Publications and source records attributed to Weber, K..

25 records · Page 2Linked to original sources

bioRxiv2019

No title, no theme: The joined neural space between speakers and listeners during production and comprehension of multi sentence discourse

Speakers and listeners usually interact in larger discourses than single words or even single sentences. The goal of the present study was to identify the neural bases reflecting how the mental representation of the situation denoted in a multi-sentence discourse (situation model) is constructed and shared between speakers and listeners. An fMRI study using a variant of the ambiguous text paradigm was designed. Speakers produced ambiguous texts in the scanner and listeners subsequently listened to these texts in different states of ambiguity: preceded by a highly informative, intermediately informative or no title at all. Conventional BOLD activation analyses in listeners, as well as inter-subject correlation analyses between the speakers and the listeners hemodynamic time courses were performed. Critically, only the processing of disambiguated, coherent discourse with an intelligible situation model representation involved (shared) activation in bilateral lateral parietal and medial prefrontal regions. This shared spatiotemporal pattern of brain activation between the speaker and the listener suggests that the process of memory retrieval in medial prefrontal regions and the binding of retrieved information in the lateral parietal cortex constitutes a core mechanism underlying the communication of complex conceptual representations.

neuroscience↗

bioRxiv2019

Speaking in the brain: The interaction between words and syntax in producing sentences

This neuroimaging study investigated the neural infrastructure of sentence-level language production. We compared brain activation patterns, as measured with BOLD-fMRI, during production of sentences which differed in verb argument structures (intransitives, transitives, ditransitives) and the lexical status of the verb (known verbs or pseudo-verbs). An example for the type of sentence to be produced started a mini-block of six sentences with the same structure. For each trial, participants were first given the (pseudo-)verb followed by three geometric shapes to serve as verb arguments in the sentences. Production of sentences with known verbs yielded greater activation compared to those with pseudo-verbs in the core language network of left inferior frontal gyrus, the left posterior middle temporal gyrus, and a more posterior middle temporal region extending into the angular gyrus (LpMTG/AG), analogous to effects observed in language comprehension. Increasing the number of verb arguments led to greater activation in an overlapping left pMTG/AG area, particularly for known verbs, as well as in the bilateral precuneus. Thus, producing sentences with more complex structures using existing verbs lead to increased activation in the language network, suggesting some reliance on memory retrieval of stored lexical-syntactic information during sentence production. This study thus provides evidence from sentence-level language production in line with functional models of the language network that have so far been mainly based on single word production, comprehension and processing in aphasia.

neuroscience↗

bioRxiv2019

Learning lexical-syntactic biases: An fMRI study on how we connect words and syntactic information

Language processing often involves learning new words and how they relate to each other. These relations are realized through syntactic information connected to a word, e.g. a word can be verb or a noun, or both, like the word run. In a behavioral and an fMRI task we showed that words and their syntactic properties, i.e. lexical items which were either syntactically ambiguous or unambiguous, can be learned through the probabilities of co-occurrence in an exposure session and subsequently used in a production task. Novel words were processed within regions of the language network (left inferior frontal and posterior middle temporal gyrus) and more syntactic options led to higher activations herein, even when the words were shown in isolation, suggesting combined lexical-syntactic representation. When words were shown in untrained grammatical contexts, activation in left inferior frontal cortex increased. This might reflect competition between the newly learned representation and the presented information. The results elucidate the lexical nature of the neural representations of lexical-syntactic information within the language network and the specific role of the left inferior frontal cortex in unification of the novel words with the surrounding context.

neuroscience↗

bioRxiv2019

Laminar Specific fMRI Reveals Directed Interactions in Distributed Networks During Language Processing

Laminar resolution, functional magnetic resonance imaging (lfMRI) is a noninvasive technique with the potential to distinguish top-down and bottom-up signal contributions on the basis of laminar specific interactions between distal regions. Hitherto, lfMRI could not be demonstrated for either whole-brain distributed networks or for complex cognitive tasks. We show that lfMRI can reveal whole-brain directed networks during word reading. We identify distinct, language critical regions based on their association with the top-down signal stream and establish lfMRI for the noninvasive assessment of directed connectivity during task performance.

neuroscience↗

bioRxiv2018

Sentence processing is modulated by the current linguistic environment and a priori information: An fMRI study

Words are not processed in isolation but in rich contexts that are used to modulate and facilitate language comprehension. Here, we investigate distinct neural networks underlying two types of contexts. Firstly, the current linguistic environment, presented as the relative frequencies of two syntactic structures (prepositional object (PO) and double-object (DO)), which would either follow everyday linguistic experience or not. Secondly, preference towards one or the other structure depending on the verb; learned in everyday language use and stored in memory. German participants were reading PO and DO sentences in German while brain activity was measured with functional magnetic resonance imaging. Firstly, the anterior cingulate cortex (ACC) showed a pattern of activation that integrated the current linguistic environment with everyday linguistic experience. When the input did not match everyday experience, the unexpectedly frequent structure showed higher activation in the ACC than the other conditions and more connectivity from the ACC to posterior parts of the language network. Secondly, verb-based surprisal of seeing a structure given a verb (PO verb preference but DO structure presentation) resulted, within the language network (left inferior frontal and left middle/superior temporal gyrus) and the precuneus, in increased activation compared to a predictable situation. In conclusion, 1) beyond the canonical language network, brain areas engaged in cognitive control, such as the ACC, might use the statistics of syntactic structures to facilitate language comprehension, 2) the language network is directly engaged in processing verb preferences. These two networks show distinct influences on sentence processing.

neuroscience↗

bioRxiv2018

A common goodness-of-fit framework for neural population models using marked point process time-rescaling

A critical component of any statistical modeling procedure is the ability to assess the goodness-of-fit between a model and observed data. For neural spike train models of individual neurons, many goodness-of-fit measures rely on the time-rescaling theorem to assess the statistical properties of rescaled spike times. Recently, there has been increasing interest in statistical models that describe the simultaneous spiking activity of neuron populations, either in a single brain region or across brain regions. Classically, such models have used spike sorted data to describe relationships between the identified neurons, but more recently clusterless modeling methods have been used to describe population activity using a single model. Here we develop a generalization of the time-rescaling theorem that enables comprehensive goodness-of-fit analysis for either of these classes of population models. We use the theory of marked point processes to model population spiking activity, and show that under the correct model, each spike can be rescaled individually to generate a uniformly distributed set of events in time and the space of spike marks. After rescaling, multiple well-established goodness-of-fit procedures and statistical tests are available. We demonstrate the application of these methods both to simulated data and real population spiking in rat hippocampus.

neuroscience↗

bioRxiv2017

Loss of Wt1 in the murine spinal cord alters interneuron composition and locomotion

Rhythmic and patterned locomotion is driven by spinal cord neurons that form neuronal circuits, referred to as central pattern generators (CPGs). Recently, dI6 neurons were suggested to participate in the control of locomotion. The dI6 neurons can be subdivided into three populations, one of which expresses the Wilms tumor suppressor gene Wt1. However, the role that Wt1 exerts on these cells is not understood. Here, we aimed to identify behavioral changes and cellular alterations in the spinal cord associated with Wt1 deletion. Locomotion analyses of mice with neuron-specific Wt1 deletion revealed that these mice ran slower than controls with a decreased stride frequency and an increased stride length. These mice showed changes in their fore-hindlimb coordination, which were accompanied by a loss of contralateral projections in the spinal cord. Neonates with Wt1 deletion displayed an increase in uncoordinated hindlimb movements and their motor neuron output was arrhythmic with a decreased frequency. The population size of dI6, V0 and V2a neurons in the developing spinal cord of conditional Wt1 mutants was significantly altered. These results show that the development of particular dI6 neurons depends on Wt1 expression and loss of Wt1 is associated with alterations in locomotion.

neuroscience↗