Biology subjects

Auksztulewicz, R.

Publications and source records attributed to Auksztulewicz, R..

25 records · Page 2Linked to original sources

bioRxiv2021

Spontaneous neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Spontaneous fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on invasive electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.

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bioRxiv2020

Memory Transfer of Random Time Patterns Across Modalities

Perception is sensitive to statistical regularities in the environment, including temporal characteristics of sensory inputs. Interestingly, temporal patterns implicitly learned within one modality can also be recognised in another modality. However, it is unclear how cross-modal learning transfer affects neural responses to sensory stimuli. Here, we recorded neural activity of human volunteers (N=24, 12 females, 12 males) using electroencephalography (EEG), while participants were exposed to brief sequences of randomly-timed auditory or visual pulses. Some trials consisted of a repetition of the temporal pattern within the sequence, and subjects were tasked with detecting these trials. Unknown to the participants, some trials reappeared throughout the experiment, enabling implicit learning. Replicating previous behavioural findings, we showed that participants benefit from temporal information learned in audition, and that they can apply this information to stimuli presented in vision. Such memory transfer was not observed from vision to audition. However, using an analysis of EEG response learning curves, we showed that learning temporal structures both within and across modalities modulates single-trial EEG response amplitudes in both conditions (audition to vision and vision to audition). Interestingly, the neural correlates of temporal learning within modalities relied on modality-specific brain regions, while learning transfer affected activity in frontal regions, suggesting distinct mechanisms. The cross-modal effect could be linked to frontal beta-band activity. The neural effects of learning transfer were similar both when temporal information learned in audition was transferred to visual stimuli and vice versa. Thus, both modality-specific mechanisms for learning of temporal information, and general mechanisms which mediate learning transfer across modalities, have distinct physiological signatures that are observable in the EEG.

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bioRxiv2020

Do auditory mismatch responses differ between acoustic features?

Mismatch negativity (MMN) is the electroencephalographic (EEG) waveform obtained by subtracting event-related potential (ERP) responses evoked by unexpected deviant stimuli from responses evoked by expected standard stimuli. While the MMN is thought to reflect an unexpected change in an ongoing, predictable stimulus, it is unknown whether MMN responses evoked by changes in different stimulus features have different magnitudes, latencies, and topographies. The present study aimed to investigate whether MMN responses differ depending on whether sudden stimulus change occur in pitch, duration, location or vowel identity respectively. To calculate ERPs to standard and deviant stimuli, EEG signals were recorded in normal-hearing participants (N=20; 13 males, 7 females) who listened to roving oddball sequences of artificial syllables. In the roving paradigm, any given stimulus is repeated several times to form a standard, and then suddenly replaced with a deviant stimulus which differs from the standard. Here, deviants differed from preceding standards along one of four features (pitch, duration, vowel or interaural level difference). The feature levels were individually chosen to match behavioral discrimination performance. We identified neural activity evoked by unexpected violations along all four acoustic dimensions. Evoked responses to deviant stimuli increased in amplitude relative to the responses to standard stimuli. A univariate (channel-by-channel) analysis yielded no significant differences between MMN responses following violations of different features. However, in a multivariate analysis (pooling information from multiple EEG channels), acoustic features could be decoded from the topography of mismatch responses, although at later latencies than those typical for MMN. These results support the notion that deviant feature detection may be subserved by a different process than general mismatch detection.

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bioRxiv2020

Neural correlates of auditory pattern learning in the auditory cortex

Learning of new auditory stimuli requires repetitive exposure to the stimulus. Fast and implicit learning of sounds presented at random times enables efficient auditory perception. However, it is unclear how such sensory encoding is processed on a neural level. We investigated neural responses that are developed from a passive, repetitive exposure to a specific sound in the auditory cortex of anesthetized rats, using electrocorticography. We presented a series of random sequences that are generated afresh each time, except for a specific reference sequence that remains constant and re-appears at random times across trials. We compared induced activity amplitudes between reference and fresh sequences. Neural responses from both primary and non-primary auditory cortical regions showed significantly decreased induced activity amplitudes for reference sequences compared to fresh sequences, especially in the beta band. This is the first study showing that neural correlates of auditory pattern learning can be evoked even in anesthetized, passive listening animal models.

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bioRxiv2019

Dissociable neural effects of temporal expectations due to passage of time and contextual probability

The human brain is equipped with complex mechanisms to track the changing probability of events in time. While the passage of time itself usually leads to a mounting expectation, context can provide additional information about when events are likely to happen. In this study we dissociate these two sources of temporal expectation in terms of their neural correlates and underlying brain connectivity patterns. We analysed magnetoencephalographic (MEG) data acquired from N=24 healthy participants listening to auditory stimuli. These stimuli could be presented at different temporal intervals but occurred most often at intermediate intervals, forming a contextual probability distribution. Evoked MEG response amplitude was sensitive to both passage of time and contextual probability, albeit at different latencies: the effects of passage of time were observed earlier than the effects of context. The underlying sources of MEG activity were also different across the two types of temporal prediction: the effects of passage of time were localised to early auditory regions and superior temporal gyri, while context was additionally linked to activity in inferior parietal cortices. Finally, these differences were modelled using biophysical (dynamic causal) modelling: passage of time was explained in terms of widespread gain modulation and decreased prediction error signalling at lower levels of the hierarchy, while contextual expectation led to more localised gain modulation and decreased prediction error signalling at higher levels of the hierarchy. These results present a comprehensive account of how independent sources of temporal prediction may be differentially expressed in cortical circuits.\n\nHIGHLIGHTS- Predictability of tone onset times affects auditory network connectivity\n- Foreperiod and distribution of events in time have dissociable neural substrates\n- Decreased prediction error at different levels of cortical hierarchy

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bioRxiv2019

Hierarchical learning of statistical regularities over multiple timescales of sound sequence processing: A dynamic causal modelling study

The nervous system is endowed with predictive capabilities, updating neural activity to reflect recent stimulus statistics in a manner which optimises processing of expected future states. This process has previously been formulated within a predictive coding framework, where sensory input is either \"explained away\" by accurate top-down predictions, or leads to a salient prediction error which triggers an update to the existing prediction when inaccurate. However, exactly how the brain optimises predictive processes in the stochastic and multi-faceted real-world environment remains unclear. Auditory evoked potentials have proven a useful measure of monitoring unsupervised learning of patterning in sound sequences through modulations of the mismatch negativity component which is associated with \"change detection\" and widely used as a proxy for indexing learnt regularities. Here we used dynamic causal modelling to analyse scalp-recorded auditory evoked potentials collected during presentation of sound sequences consisting of multiple, nested regularities and extend on previous observations of pattern learning restricted to the scalp level or based on single-outcome events. Patterns included the regular characteristics of the two tones presented, consistency in their relative probabilities as either common standard (p = .875) or rare deviant (p = .125), and the regular rate at which these tone probabilities alternated. Significant changes in connectivity reflecting a drop in the precision of prediction errors based on learnt patterns were observed at three points in the sound sequence, corresponding to the three hierarchical levels of nested regularities: (1) when an unexpected \"deviant\" sound was encountered; (2) when the probabilities of the two tonal states altered; and (3) when there was a change in rate at which probabilities in tonal state changed. These observations provide further evidence of simultaneous pattern learning over multiple timescales, reflected through changes in neural activity below the scalp.\n\nAuthor summaryOur physical environment is comprised of regularities which give structure to our world. This consistency provides the basis for experiential learning, where we can increasingly master our interactions with our surroundings based on prior experience. This type of learning also guides how we sense and perceive the world. The sensory system is known to reduce responses to regular and predictable patterns of input, and conserve neural resources for processing input which is new and unexpected. Temporal pattern learning is particularly important for auditory processing, in disentangling overlapping sound streams and deciphering the information value of sound. For example, understanding human language requires an exquisite sensitivity to the rhythm and tempo of speech sounds. Here we elucidate the sensitivity of the auditory system to concurrent temporal patterning during a sound sequence consisting of nested patterns over three timescales. We used dynamic causal modelling to demonstrate that the auditory system monitors short, intermediate and longer-timescale patterns in sound simultaneously. We also show that these timescales are each represented by distinct connections between different brain areas. These findings support complex interactions between different areas of the brain as responsible for the ability to learn sophisticated patterns in sound even without conscious attention.

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bioRxiv2017

NMDA receptor blockade causes selective prefrontal disinhibition in a roving auditory oddball paradigm

N-methyl-D-aspartate receptors (NMDARs) are expressed widely throughout the human cortex. Yet disturbances in NMDAR transmission - as implicated in patients with schizophrenia or pharmacologically induced - can cause a regionally specific set of electrophysiological effects. Here, we present a double-blind placebo-controlled study of the effects of the NMDAR blocker ketamine in human volunteers. We employ a marker of auditory learning and putative synaptic plasticity - the mismatch negativity - in a roving auditory oddball paradigm. Using recent advances in Bayesian modelling of group effects in dynamic causal modelling, we fit biophysically plausible network models of the auditory processing hierarchy to whole-scalp evoked response potential recordings. This allowed us to identify the regionally specific effects of ketamine in a distributed network of interacting cortical sources. Under placebo, our analysis replicated previous findings regarding the effects of stimulus repetition and deviance on connectivity within the auditory hierarchy. Crucially, we show that the effect of ketamine is best explained as a selective change in intrinsic inhibition, with a pronounced ketamine-induced reduction of inhibitory interneuron connectivity in frontal sources. These results are consistent with findings from invasive recordings in animal models exposed to NMDAR blockers, and provide evidence that inhibitory-interneuron specific NMDAR dysfunction may be sufficient to explain electrophysiological abnormalities of sensory learning induced by ketamine in human subjects.\n\nO_TEXTBOXSignificance StatementDysfunction of N-methyl-D-aspartate receptors (NMDARs) has been implicated in a range of psychopathologies, yet mechanisms translating receptor-level abnormalities to whole-brain pathology remain unclear. We use computational modelling to infer microcircuit mechanisms by which ketamine, an NMDAR-blocker, alters brain responses to changing sequences of sounds that rely on sensory learning. This dynamic causal modelling (DCM) approach shows that ketamine-effects can be explained with brain region specific changes in inhibitory interneuron coupling alone, with a striking reduction in inhibition in the prefrontal cortex. This suggests that NMDAR-effects on excitation-inhibition balance differ between brain regions, and provides evidence from healthy human subjects that NMDAR blockade may cause prefrontal cortex disinhibition, one of the mechanisms hypothesised to underlie psychopathology in schizophrenia.\n\nC_TEXTBOX

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