Biology subjects

Hanslmayr, S.

Publications and source records attributed to Hanslmayr, S..

12 recordsLinked to original sources

bioRxiv2018

Theta oscillations show impaired interference detection in the elderly during selective memory retrieval

Seemingly effortless tasks, such as recognizing faces and retrieving names, become significantly harder as people get older. These age-related difficulties may be partially due to the concurrent activation of related competitors. However, it remains unclear whether older adults struggle with detecting an early interference signal or with suppressing irrelevant competitors once competition is detected. To investigate this question, we used the retrieval practice paradigm, shown to elicit interference, while recording electrophysiological activity in young and older adults. In two experiments, young participants showed the typical Retrieval Induced Forgetting (RIF) effect whereas the elderly did not. Neurally, young adults were more capable to detect interference than the older, as evidenced by an increase in mid-frontal theta power (~4-8Hz). This efficient interference detection allowed young adults to recruit inhibitory mechanisms that overcome competition, as traced by a theta power reduction across retrieval cycles. No such reduction was found for the elderly, indicating that the lack of an early interference detection signal renders older adults unable to recruit memory selection mechanisms, eliminating RIF.\n\nAUTHORS NOTEThis research was supported by the doctoral research grants AP2009-2215 to C.S.F and BES-2013-066842 to M.J.M.; by grants PSI2012-33625; PSI2015-65502-C2-1-P from the Spanish Ministry of Economy and Competiveness, and by the Economic Council of the Andalusian Government P08-HUM-03600-Feder and P12-CTS-2369-Feder to T.B.\n\nDeclaration of interestThe authors have no conflicts of interest to disclose

neuroscience↗

bioRxiv2018

Two spatially distinct posterior alpha sources fulfill different functional roles in attention

Directing attention helps to extract relevant information and suppress distracters. Alpha brain oscillations (8-12Hz) play a fundamental role in this process, with a power decrease facilitating processing of important information and power increase inhibiting brain regions processing irrelevant information. Evidence for this phenomenon arises from visual attention studies (Worden et al., 2000), however, the effect also exists in other modalities, including the somatosensory system (Haegens et al., 2011) and inter-sensory attention tasks (Foxe and Snyder, 2011). We investigated what happens when attention is divided between two modalities using both a multi- and unimodal attention paradigm while recording EEG over 128 scalp electrodes in two separate experiments. In Experiment 1 participants divided their attention between the visual and somatosensory modality to determine the temporal or spatial frequency of a target stimulus (vibrotactile stimulus or Gabor grating). In Experiment 2, participants divided attention between two visual hemifields to identify the orientation of a target Gabor grating. In both experiments, pre-stimulus alpha power in visual areas decreased linearly with increasing attention to visual stimuli. In contrast, alpha power in parietal areas showed lower pre-stimulus alpha power when attention was divided between modalities, compared to unimodal attention. These results suggest that there are two different alpha sources, where one reflects the visual spotlight of attention and the other reflects attentional effort. To our knowledge, this is the first study to show that attention recruits two spatially distinct alpha sources in occipital and parietal brain regions, which act simultaneously but serve different functions in attention.\n\nSIGNIFICANCE STATEMENTAttention to one spatial location/sensory modality leads to power changes of alpha oscillations (~10Hz) with decreased power over regions processing relevant information and power increases to actively inhibit areas processing to-be-ignored information. Here, we used detailed source modelling to investigate EEG data recorded during separate uni-modal (visual) and multi- (visual and somatosensory) attention tasks. Participants either focused their attention on one modality/spatial location or directed it to both. We show for the first time two distinct alpha sources are active simultaneously but play different roles. A sensory (visual) alpha source was linearly modulated by attention representing the visual spotlight of attention. In contrast, a parietal alpha source was modulated by attentional effort, showing lowest alpha power when attention was divided.

neuroscience↗

bioRxiv2018

Addressing challenges of high spatial resolution, UHF field fMRI for group analysis of higher-order cognitive tasks; an inter-sensory task directing attention between visual and somatosensory domains.

Functional MRI at ultra-high field (UHF, [≥]7T) provides significant increases in BOLD contrast-to-noise ratio (CNR) compared with conventional field strength (3T), and has been exploited for reduced field-of-view, high spatial resolution mapping of primary sensory areas. Applying these high spatial resolution methods to investigate whole brain functional responses to higher-order cognitive tasks leads to a number of challenges, in particular how to perform robust group-level statistical analyses.\n\nThis study addresses these challenges using an inter-sensory cognitive task which modulates top-down attention at graded levels between the visual and somatosensory domains. At the individual level, highly focal functional activation to the task and task difficulty (modulated by attention levels) were detectable due to the high CNR at UHF. However, to assess group level effects, both anatomical and functional variability must be considered during analysis. We demonstrate the importance of surface over volume normalization and the requirement of no spatial smoothing when assessing highly focal activity. Using novel group analysis on anatomically parcellated brain regions, we show that in higher cognitive areas (parietal and dorsal-lateral-prefrontal cortex) fMRI responses to graded attention levels were modulated quadratically, whilst in visual cortex and VIP, responses were modulated linearly. These group fMRI responses were not seen clearly using conventional second-level GLM analyses, illustrating the limitations of a conventional approach when investigating such focal responses in higher cognitive regions which are more anatomically variable. The approaches demonstrated here complement other advanced analysis methods such as multi-variate pattern analysis, allowing UHF to be fully exploited in cognitive neuroscience.

neuroscience↗

bioRxiv2018

Spectral fingerprints or spectral tilt? Evidence for distinct oscillatory signatures of memory formation

Decreases in low frequency power (2-30 Hz) alongside high frequency power increases (>40 Hz) have been demonstrated to predict successful memory formation. Parsimoniously this change in the frequency spectrum can be explained by one factor, a change in the tilt of the power spectrum (from steep to flat) indicating engaged brain regions. A competing view is that the change in the power spectrum contains several distinct brain oscillatory fingerprints, each serving different computations. Here, we contrast these two theories in a parallel MEG-intracranial EEG study where healthy participants and epilepsy patients, respectively, studied either familiar verbal material, or unfamiliar faces. We investigated whether modulations in specific frequency bands can be dissociated in time, space and by experimental manipulation. Both, MEG and iEEG data, show that decreases in alpha/beta power specifically predicted the encoding of words, but not faces, whereas increases in gamma power and decreases in theta power predicted memory formation irrespective of material. Critically, these different oscillatory signatures of memory encoding were evident in different brain regions. Moreover, high frequency gamma power increases occurred significantly earlier compared to low frequency theta power decreases. These results speak against a \"spectral tilt\" and demonstrate that brain oscillations in different frequency bands serve different functions for memory encoding.

neuroscience↗

bioRxiv2018

Speed of time-compressed forward replay flexibly changes in human episodic memory

Remembering information from continuous past episodes is a complex task. On the one hand, we must be able to recall events in a highly accurate way that often includes exact timing; on the other hand, we can ignore irrelevant details and skip to events of interest. We here track continuous episodes, consisting of different sub-events, as they are recalled from memory. In behavioral and MEG data, we show that memory replay is temporally compressed and proceeds in a forward direction. Neural replay is characterized by the reinstatement of temporal patterns from encoding. These fragments of activity reappear on a compressed timescale. Herein, the replay of sub-events takes longer than the transition from one sub-event to another. This identifies episodic memory replay as a dynamic process in which participants replay fragments of fine-grained temporal patterns and are able to skip flexibly across sub-events.

neuroscience↗

bioRxiv2018

Hippocampal synchrony and neocortical desynchrony cooperate to encode and retrieve episodic memories

Episodic memories hinge upon our ability to process a wide range of multisensory information and bind this information into a coherent, memorable representation. On a neural level, these two processes are thought to be supported by neocortical alpha/beta desynchronisation and hippocampal theta/gamma synchronisation, respectively. Intuitively, these two processes should couple to successfully create and retrieve episodic memories, yet this hypothesis has not been tested empirically. We address this by analysing human intracranial EEG data recorded during two associative memory tasks. We find that neocortical alpha/beta (8-20Hz) power decreases reliably precede and predict hippocampal \"fast\" gamma (60-80Hz) power increases during episodic memory formation; during episodic memory retrieval however, hippocampal \"slow\" gamma (40-50Hz) power increases reliably precede and predict later neocortical alpha/beta power decreases. We speculate that this coupling reflects the flow of information from neocortex to hippocampus during memory formation, and hippocampal pattern completion inducing information reinstatement in the neocortex during memory retrieval.\n\nSignificance StatementEpisodic memories detail our personally-experienced past. The formation and retrieval of these memories has long been thought to be supported by a division of labour between the neocortex and the hippocampus, where the former processes event-related information and the latter binds this information together. However, it remains unclear how the two regions interact. We uncover directional coupling between these regions, with power decreases in the neocortex that precede and predict power increases in the hippocampus during memory formation. Fascinatingly, this process reverses during memory retrieval, with hippocampal power increases preceding and predicting neocortical power decreases. These results suggest a bidirectional flow of information between the neocortex and hippocampus is fundamental to the formation and retrieval of episodic memories.

neuroscience↗

bioRxiv2018

Single-trial Phase Entrainment of Theta Oscillations in Sensory Regions Predicts Human Associative Memory Performance

Episodic memories are rich in sensory information and often contain integrated information from different sensory modalities. For instance, we can store memories of a recent concert with visual and auditory impressions being integrated in one episode. Theta oscillations have recently been implicated in playing a causal role synchronizing and effectively binding the different modalities together in memory. However, an open question is whether momentary fluctuations in theta synchronization predict the likelihood of associative memory formation for multisensory events. To address this question we presented movies and sounds with their luminance and volume modulated at theta (4 Hz), with a phase offset at 0{degrees} or 180{degrees} with respect to each other. This allowed us to entrain the visual and auditory cortex in a synchronous (0{degrees}) or asynchronous manner (180{degrees}). Participants were asked to remember the association between a movie and a sound while having their EEG activity recorded. Associative memory performance was significantly enhanced in the synchronous (0{degrees}) compared to the asynchronous (180{degrees}) condition. Source-level analysis demonstrated that the physical stimuli effectively entrained their respective cortical areas with a corresponding phase offset. Importantly, the strength of entrainment during encoding correlated with the efficacy of associative memory such that small phase differences between visual and auditory cortex predicted a high likelihood of correct retrieval in a later recall test. These findings suggest that theta oscillations serve a specific function in the episodic memory system: Binding the contents of different modalities into coherent memory episodes.\n\nSignificance StatementHow multi-sensory experiences are bound to form a coherent episodic memory representation is one of the fundamental questions in human episodic memory research. Evidence from animal literature suggests that the relative timing between an input and theta oscillations in the hippocampus is crucial for memory formation. We precisely controlled the timing between visual and auditory stimuli and the neural oscillations at 4 Hz using a multisensory entrainment paradigm. Human associative memory formation depends on coincident timing between sensory streams processed by the corresponding brain regions. We provide evidence for a significant role of relative timing of neural theta activity in human episodic memory on a single trial level, which reveals a crucial mechanism underlying human episodic memory.

neuroscience↗

bioRxiv2018

Reactivation of neural patterns during memory reinstatement supports encoding specificity

Encoding specificity or transfer appropriate processing state that memory benefits when items are encoded and retrieved in the same modality compared to when encoding and retrieval is conducted in different modalities. In neural terms, these effects can be expressed by a resonance process between a memory cue and a stored engram; the more the two overlap the better memory performance. We here used temporal pattern analysis in MEG to tap into this resonance process. We predicted that reactivation of sensory patterns established during encoding has opposing effects depending on whether there is a match or mismatch between the memory cue and the encoding modality. To test this prediction items were presented either visually or aurally during encoding and in a recognition test to create match (e.g. \"dog\" presented aurally during encoding and recognition) and mismatch conditions (e.g. \"dog\" presented aurally during encoding and shown visually during recognition). Memory performance was better for items in the match compared to the mismatch condition. MEG results showed that memory benefitted from neural pattern reinstatement only in the match condition, but suffered from reinstatement in the mismatch condition. These behavioural and neural effects were asymmetric in that they were only obtained for aurally encoded words but not for visually encoded words. A simple computational model was generated in order to simulate these opposing effects of neural pattern reactivation on memory performance. We argue that these results suggest that reactivation of neural patterns established during encoding underlies encoding specificity or transfer appropriate processing.

neuroscience↗

bioRxiv2017

Replay of Stimulus Specific Temporal Patterns during Associative Memory Formation

Forming a memory often entails the association of recent experience with present events. This recent experience is usually an information rich and dynamic representation of the world around us. We here show that associating a static cue with a previously shown dynamic stimulus, yields a detectable, dynamic representation of this stimulus in working memory. We further implicate this representation in the decrease of low-frequency power ([~]4-30 Hz) in the ongoing electroencephalogram (EEG), which is a well-known correlate of successful memory formation. The maintenance of content specific patterns in desynchronizing brain oscillations was observed in two sensory domains, i.e. in a visual and in an auditory condition. Together with previous results, these data suggest a mechanism that generalizes across domains and processes, in which the decrease in oscillatory power allows for the dynamic representation of information in ongoing brain oscillations.

neuroscience↗

bioRxiv2017

Across-subjects classification of stimulus modality from human MEG high frequency activity

Single-trial analyses have the potential to uncover meaningful brain dynamics that are obscured when averaging across trials. However, low signal-to-noise ratio (SNR) can impede the use of single-trial analyses and decoding methods. In this study, we investigate the applicability of a single-trial approach to decode stimulus modality from magnetoencephalography (MEG) high frequency activity. In order to classify the auditory versus visual presentation of words, we combine beamformer source reconstruction with the random forest classification method. To enable group level inference, the classification is embedded in an across-subjects framework.\n\nWe show that single-trial gamma SNR allows for good classification performance (accuracy across subjects: 66.44 %). This implies that the characteristics of high frequency activity have a high consistency across trials and subjects. The random forest classifier assigned informational value to activity in both auditory and visual cortex with high spatial specificity. Across time, gamma power was most informative during stimulus presentation. Among all frequency bands, the 75-95 Hz band was the most informative frequency band in visual as well as in auditory areas. Especially in visual areas, a broad range of gamma frequencies (55-125 Hz) contributed to the successful classification.\n\nThus, we demonstrate the feasibility of single-trial approaches for decoding the stimulus modality across subjects from high frequency activity and describe the discriminative gamma activity in time, frequency, and space.\n\nAuthor SummaryAveraging brain activity across trials is a powerful way to increase signal-to-noise ratio in MEG data. This approach, however, potentially obscures meaningful brain dynamics that unfold on the single-trial level. Single-trial analyses have been successfully applied to time domain or low frequency oscillatory activity; its application to MEG high frequency activity is hindered by the low amplitude of these signals. In the present study, we show that stimulus modality (visual versus auditory presentation of words) can successfully be decoded from single-trial MEG high frequency activity by combining source reconstruction with a random forest classification algorithm. This approach reveals patterns of activity above 75 Hz in both visual and auditory cortex, highlighting the importance of high frequency activity for the processing of domain-specific stimuli. Thereby, our results extend prior findings by revealing high-frequency activity in auditory cortex related to auditory word stimuli in MEG data. The adopted across-subjects framework furthermore suggests a high inter-individual consistency in the high frequency activity patterns.

neuroscience↗

bioRxiv2017

The Sync/deSync model: How a synchronized hippocampus and a de-synchronized neocortex code memories

Neural oscillations are important for memory formation in the brain. The de-synchronisation of Alpha (10Hz) oscillations in the neo-cortex has been shown to predict successful memory encoding and retrieval. However, when engaging in learning, it has been found that the hippocampus synchronises in Theta (4Hz) oscillations, and that learning is dependent on the phase of Theta. This inconsistency as to whether synchronisation is good for memory formation leads to confusion over which oscillations we should expect to see and where during learning paradigm experiments. This paper seeks to respond to this inconsistency by presenting a neural network model of how a well-functioning learning system could exhibit both of these phenomena, i.e. desynchronization of alpha and synchronisation of theta during successful memory encoding.\n\nWe present a spiking neural network (the Sync/deSync model) of the neo-cortical and hippocampal system. The simulated hippocampus learns through an adapted spike-time dependent plasticity rule, in which weight change is modulated by the phase of an extrinsically generated theta oscillation. Additionally, a global passive weight decay is incorporated, which is also modulated by theta phase. In this way, the Sync/deSync model exhibits theta phase-dependent long-term potentiation and long-term depression. We simulated a learning paradigm experiment and compared the oscillatory dynamics of our model with those observed in single-cell and scalp-EEG studies of the medial temporal lobe. Our Sync/deSync model suggests that both the de-synchronisation of neo-cortical Alpha and the synchronisation of hippocampal Theta are necessary for successful memory encoding and retrieval.\n\nSignificance statementA fundamental question is the role of rhythmic activation of neurons, i.e. how their firing oscillates between high and low rates. A particularly important question is how oscillatory dynamics between the neo-cortex and hippocampus contribute to memory formation. We present a spiking neural-network model of such memory formation, with the central ideas that 1) in neo-cortex, neurons need to break-out of an alpha oscillation in order to represent a stimulus (i.e. alpha desynchronises), while 2) in hippocampus, the firing of neurons at theta facilitates formation of memories (i.e. theta synchronises). Accordingly, successful memory formation is marked by reduced neo-cortical alpha and increased hippocampal theta. This pattern has been observed experimentally and gives our model its name - the Synch/deSynch model.

neuroscience↗

bioRxiv2017

Data-driven re-referencing of intracranial EEG based on independent component analysis (ICA)

Intracranial recordings from patients implanted with depth electrodes are a valuable source of information in cognitive neuroscience. They allow for the unique opportunity to record brain activity with a high spatial and temporal resolution. To extract the local signal of interest in stereotactic EEG (S-EEG) data, a common pre-processing choice is to re-reference the data with a bipolar montage.\n\nWith bipolar reference, each channel is subtracted from its neighbour in order to reduce commonalities between channels and isolate activity that is spatially confined. We here challenge the assumption that bipolar reference can effectively perform this task. We argue that in order to extract local activity, the distribution of the signal source of interest, as well as the distribution of interfering distant signals and noise sources need to be considered. Those can have a variable spatial extent and are modulated by electrode spacing, location and anatomical characteristics. Those factors are not accounted for by a fixed referencing scheme and bipolar reference can therefore not only decrease the signal to noise ratio (SNR) of the data, but also lead to mislocalization of activity and consequently to misinterpretation of results.\n\nWe promote the perspective of regarding referencing as a spatial filtering operation with fixed coefficients. As an alternative, we propose to use Independent Component Analysis (ICA), to derive filter coefficients that reflect the statistical dependencies of the data at hand. We argue that ICA performs the same task that bipolar referencing pursues, namely undoing the linear superposition of activity and can therefore be used to identify activity that is local. We first describe and demonstrate this procedure on human S-EEG recordings. In a simulation with real data, we then quantitatively show that ICA outperforms the bipolar referencing operation in sensitivity and importantly in specificity when it comes to revealing local time series from the superposition of neighbouring channels.

neuroscience↗