The representation of auditory space in the auditory cortex of anesthetized and awake mice

The ability to localize sounds is of profound importance for animals, as it enables them to detect prey and predators. In the horizontal plane, sound localization is achieved by means of binaural cues, which are processed and interpreted by the ascending auditory pathway. The auditory cortex (AC), as its primary cortical relay station, has traditionally been thought to broadly and stationary represent the contralateral hemifield of auditory space. Because prior research on space representation in the mammalian AC heavily relied on anesthetized preparations, the manner in which anesthesia influences this representation has remained elusive. Performing chronic two-photon-calcium imaging in the AC of awake and anesthetized mice, I characterized the effects of anesthesia on auditory space representation. First, anesthesia was found to impair the spatial sensitivity of neurons. Second, anesthesia constantly suppressed the representation of frontal locations biasing spatial tuning to the contralateral side. In both conditions (awake and anesthetized), the population of neurons endured a stable representation of auditory space, while single-cell spatial tuning was found to be extremely dynamic. Importantly, under both conditions no evidence for a topographical map of auditory space was found. This study is the first to chronically probe spatial tuning in the AC and likewise the first to directly assess effects of anesthesia on single-cell spatial tuning and the population code emphasizing the need for a shift towards awake preparations

Synchronization of electrophysiological responses with speech benefits syntactic information processing

In auditory neuroscience, electrophysiological synchronization to low-level acoustic and high-level linguistic features is well established—but its functional purpose for verbal information transmission is unclear. Based on prior evidence for a dependence of auditory task performance on delta-band oscillatory phase, we hypothesized that the synchronization of electrophysiological responses at delta-band frequency to the speech stimulus serves to implicitly align neural excitability with syntactic information. The experimental paradigm of our auditory EEG study uniformly distributed morphosyntactic violations across syntactic phrases of natural sentences, such that violations would occur at points differing in linguistic information content. In support of our hypothesis, we found behavioral responses to morphosyntactic violations to increase with decreasing syntactic information content—in significant correlation with delta-band phase, which had synchronized to our speech stimuli. Our findings indicate that rhythmic electrophysiological synchronization to the speech stream is a functional mechanism that may align neural excitability with linguistic information content, optimizing language comprehension

Toward the Language Oscillogenome

Language has been argued to arise, both ontogenetically and phylogenetically, from specific patterns of brain wiring. We argue that it can further be shown that core features of language processing emerge from particular phasal and cross-frequency coupling properties of neural oscillations; what has been referred to as the language ‘oscillome.’ It is expected that basic aspects of the language oscillome result from genetic guidance, what we will here call the language ‘oscillogenome,’ for which we will put forward a list of candidate genes. We have considered genes for altered brain rhythmicity in conditions involving language deficits: autism spectrum disorders, schizophrenia, specific language impairment and dyslexia. These selected genes map on to aspects of brain function, particularly on to neurotransmitter function. We stress that caution should be adopted in the construction of any oscillogenome, given the range of potential roles particular localized frequency bands have in cognition. Our aim is to propose a set of genome-to-language linking hypotheses that, given testing, would grant explanatory power to brain rhythms with respect to language processing and evolution

Toward the Language Oscillogenome

Language has been argued to arise, both ontogenetically and phylogenetically, from specific patterns of brain wiring. We argue that it can further be shown that core features of language processing emerge from particular phasal and cross-frequency coupling properties of neural oscillations; what has been referred to as the language ‘oscillome.’ It is expected that basic aspects of the language oscillome result from genetic guidance, what we will here call the language ‘oscillogenome,’ for which we will put forward a list of candidate genes. We have considered genes for altered brain rhythmicity in conditions involving language deficits: autism spectrum disorders, schizophrenia, specific language impairment and dyslexia. These selected genes map on to aspects of brain function, particularly on to neurotransmitter function. We stress that caution should be adopted in the construction of any oscillogenome, given the range of potential roles particular localized frequency bands have in cognition. Our aim is to propose a set of genome-to-language linking hypotheses that, given testing, would grant explanatory power to brain rhythms with respect to language processing and evolution

Testing Low-Frequency Neural Activity in Sentence Understanding

Human language has the unique characteristic where we can create infinite and novel phrases or sentences; this stems from the ability of composition, which allows us to combine smaller units into bigger meaningful units. Composition involves us following syntactic rules stored in memory and building well-formed structures incrementally. Research has shown that neural circuits can be associated with cognitive faculties such as memory and language and there is evidence indicating where and when the neural indices of the processing of composition are. However, it is not yet clear "how" neural circuits actually implement compositional processes. This dissertation aims to probe "how" composition of meaning is represented by neural circuits by investigating the role of low-frequency neural activity in carrying out composition. Neuroelectric signals were recorded with Electroencephalography (EEG) to examine the functional interpretation of low-frequency neural activity in the so-called delta band of 0.5 to 3 Hz. Activities in this band have been associated with the processing of syntactic structures (Ding et al. 2016). First, whether these activities are indeed associated with hierarchy remains under debate. This dissertation uses a novel condition in which the same words are presented, but their order is changed to remove the syntactic structure. Only entrainment with syllables was found in this "reversed" condition, supporting the hypothesis that neural activities in the delta band entrain to abstract syntactic structures. Second, we test the timing for language users to combine words and comprehend sentences. How comprehension correlates with this low-frequency neural activity and whether it represents endogenous neural response or evoked response remains unclear. This dissertation manipulates the length of syllables and regularity between syllables to test the hypotheses. The results support the view that this neural activity reflects endogenous response and suggest that it reflects top-down processing. Third, what semantic information modulates this low-frequency neural activity is unknown. This dissertation examines several semantic variables typically associated with different aspects of semantic processing. The stimuli are created by varying the statistical association between words, world knowledge, and the conceptual results of semantic composition. The current results suggest that low-frequency neural activity is not driven by semantic processing. Based on the above findings, we propose that neural activities in the delta band reflect top-down predictive processing that involves syntactic information directly but not semantic information.PHDLinguisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169907/1/chiawenl_1.pd