Characterizing multi-word speech production using event-related potentials

Abstract:

Event‐related potentials (ERPs) derived from electroencephalography (EEG) have proven useful for understanding linguistic processes during language perception and production. Words are commonly produced in sequences, yet most ERP studies have used single‐word experimental designs. Single‐word designs reduce potential ERP overlap in word sequence production. However, word sequence production engages brain mechanisms in different ways than single word production. In particular, speech monitoring and planning mechanisms are more engaged than for single words since several words must be produced in a short period of time. This study evaluates the feasibility of recording ERP components in the context of word sequence production, and whether separate components could be isolated for each word. Scalp EEG data were acquired, while participants recited word sequences from memory at a regular pace, using a tongue‐twister paradigm. The results revealed fronto‐central error‐related negativity, previously associated with speech monitoring, which could be distinguished for each word. Its peak amplitude was sensitive to Cycle and Phonological Similarity. However, an effect of sequential production was also observable on baseline measures, indicating baseline shifts throughout the word sequence due to concurrent sustained medial‐frontal EEG activity. We also report a late left anterior negativity (LLAN), associated with verbal response planning and execution, onsetting around 100 ms before the first word in each cycle and sustained throughout the rest of the cycle. This work underlines the importance of considering the contribution of transient and sustained EEG activity on ERPs, and provides evidence that ERPs can be used to study sequential word production.

Authors:

• Stephanie K. Ries

• Svetlana Pinet

• N. Bonnie Nozari

• Robert T. Knight

Date: 2021

DOI: https://doi.org/10.1111/psyp.13788

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Distinct electrophysiological signatures of task-unrelated and dynamic thoughts

Abstract:

Humans spend much of their lives engaging with their internal train of thoughts. Traditionally, research focused on whether or not these thoughts are related to ongoing tasks, and has identified reliable and distinct behavioral and neural correlates of task-unrelated and task-related thought. A recent theoretical framework highlighted a different aspect of thinking—how it dynamically moves between topics. However, the neural correlates of such thought dynamics are unknown. The current study aimed to determine the electrophysiological signatures of these dynamics by recording electroencephalogram (EEG) while participants performed an attention task and periodically answered thought-sampling questions about whether their thoughts were 1) task-unrelated, 2) freely moving, 3) deliberately constrained, and 4) automatically constrained. We examined three EEG measures across different time windows as a function of each thought type: stimulus-evoked P3 event-related potentials and non–stimulus-evoked alpha power and variability. Parietal P3 was larger for task-related relative to task-unrelated thoughts, whereas frontal P3 was increased for deliberately constrained compared with unconstrained thoughts. Frontal electrodes showed enhanced alpha power for freely moving thoughts relative to non-freely moving thoughts. Alpha-power variability was increased for task-unrelated, freely moving, and unconstrained thoughts. Our findings indicate distinct electrophysiological patterns associated with task-unrelated and dynamic thoughts, suggesting these neural measures capture the heterogeneity of our ongoing thoughts.

Authors:

• Julia WY Kam

• Zachary C Irving

• Caitlin Mills

• Shawn Patel

• Alison Gopnik

• Robert T Knight

Date: 2021

DOI: https://doi.org/10.1073/pnas.2011796118

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Fronto-temporal regulation of subjective value to suppress impulsivity in intertemporal choices

Abstract:

Impulsive decisions arise from preferring smaller but sooner rewards compared to larger but later rewards. How neural activity and attention to choice alternatives contribute to reward decisions during temporal discounting is not clear. Here we probed (i) attention to and (ii) neural representation of delay and reward information in humans (both sexes) engaged in choices. We studied behavioral and frequency specific dynamics supporting impulsive decisions on a fine-grained temporal scale using eye tracking and magnetoencephalographic (MEG) recordings. In one condition participants had to decide for themselves but pretended to decide for their best friend in a second prosocial condition, which required perspective taking. Hence, conditions varied in the value for themselves versus that pretending to choose for another person. Stronger impulsivity was reliably found across three independent groups for prosocial decisions. Eye tracking revealed a systematic shift of attention from the delay to the reward information and differences in eye tracking between conditions predicted differences in discounting. High frequency activity (HFA: 175-250 Hz) distributed over right fronto-temporal sensors correlated with delay and reward information in consecutive temporal intervals for high value decisions for oneself but not the friend. Collectively the results imply that the HFA recorded over fronto-temporal MEG sensors plays a critical role in choice option integration.

Authors:

• Stefan Dürschmid

• Andre Maric

• Marcel S Kehl

• Robert T Knight

• Hermann Hinrichs

• Hans-Jochen Heinz

Date: 2020

DOI: https://doi.org/10.1523/JNEUROSCI.1196-20.2020

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Parameterizing neural power spectra into periodic and aperiodic components

Abstract:

Electrophysiological signals exhibit both periodic and aperiodic properties. Periodic oscillations have been linked to numerous physiological, cognitive, behavioral and disease states. Emerging evidence demonstrates that the aperiodic component has putative physiological interpretations and that it dynamically changes with age, task demands and cognitive states. Electrophysiological neural activity is typically analyzed using canonically defined frequency bands, without consideration of the aperiodic (1/f-like) component. We show that standard analytic approaches can conflate periodic parameters (center frequency, power, bandwidth) with aperiodic ones (offset, exponent), compromising physiological interpretations. To overcome these limitations, we introduce an algorithm to parameterize neural power spectra as a combination of an aperiodic component and putative periodic oscillatory peaks. This algorithm requires no a priori specification of frequency bands. We validate this algorithm on simulated data, and demonstrate how it can be used in applications ranging from analyzing age-related changes in working memory to large-scale data exploration and analysis.

Authors:

• Thomas Donoghue

• Matar Haller

• Erik J Peterson

• Paroma Varma

• Priyadarshini Sebastian

• Richard Gao

• Torben Noto

• Antonio H Lara

• Joni D Wallis

• Robert T Knight

• Avgusta Shestyuk

• Bradley Voytek

Date: 2020

DOI: https://doi.org/10.1038/s41593-020-00744-x

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Direct brain recordings reveal occipital cortex involvement in memory development

Abstract:

Processing of low-level visual information shows robust developmental gains through childhood and adolescence. However, it is unknown whether low-level visual processing in the occipital cortex supports age-related gains in memory for complex visual stimuli. Here, we examined occipital alpha activity during visual scene encoding in 24 children and adolescents, aged 6.2–20.5 years, who performed a subsequent memory task while undergoing electrocorticographic recording. Scenes were classified as high- or low-complexity by the number of unique object categories depicted. We found that recognition of high-complexity, but not low-complexity, scenes increased with age. Age was associated with decreased alpha power and increased instantaneous alpha frequency during the encoding of subsequently recognized high- compared to low-complexity scenes. Critically, decreased alpha power predicted improved recognition of high-complexity scenes in adolescents. These findings demonstrate how the functional maturation of the occipital cortex supports the development of memory for complex visual scenes.

Authors:

• Qin Yin

• Elizabeth L Johnson

• Lingfei Tang

• Kurtis I Auguste

• Robert T Knight

• Eishi Asano

• Noa Ofen

Date: 2020

DOI: https://doi.org/10.1016/j.neuropsychologia.2020.107625

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Diverse Temporal Dynamics of Repetition Suppression Revealed by Intracranial Recordings in the Human Ventral Temporal Cortex

Abstract:

Repeated stimulus presentations commonly produce decreased neural responses—a phenomenon known as repetition suppression (RS) or adaptation—in ventral temporal cortex (VTC) of humans and nonhuman primates. However, the temporal features of RS in human VTC are not well understood. To fill this gap in knowledge, we utilized the precise spatial localization and high temporal resolution of electrocorticography (ECoG) from nine human subjects implanted with intracranial electrodes in the VTC. The subjects viewed nonrepeated and repeated images of faces with long-lagged intervals and many intervening stimuli between repeats. We report three main findings: 1) robust RS occurs in VTC for activity in high-frequency broadband (HFB), but not lower-frequency bands; 2) RS of the HFB signal is associated with lower peak magnitude (PM), lower total responses, and earlier peak responses; and 3) RS effects occur early within initial stages of stimulus processing and persist for the entire stimulus duration. We discuss these findings in the context of early and late components of visual perception, as well as theoretical models of repetition suppression.

Authors:

• Vinitha Rangarajan

• Corentin Jacques

• Robert T Knight

• Kevin S Weiner

• Kalanit Grill-Spector

Date: 2020

DOI: https://doi.org/10.1093/cercor/bhaa173

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Multiple sequential prediction errors during reward processing in the human brain

Summary:

Recent developments in reinforcement learning, cognitive control, and systems neuroscience highlight the complimentary roles in learning of valenced reward prediction errors (RPEs) and non-valenced salience prediction errors (PEs) driven by the magnitude of surprise. A core debate in reward learning focuses on whether valenced and non-valenced PEs can be isolated in the human electroencephalogram (EEG). Here, we combine behavioral modeling and single-trial EEG regression revealing a sequence of valenced and non-valenced PEs in an interval timing task dissociating outcome valence, magnitude, and probability. Multiple regression across temporal, spatial, and frequency dimensions revealed a spatio-tempo-spectral cascade from valenced RPE value represented by the feedback related negativity event-related potential (ERP) followed by non-valenced RPE magnitude and outcome probability effects indexed by subsequent P300 and late frontal positivity ERPs. The results show that learning is supported by a sequence of multiple PEs evident in the human EEG.

Authors:

• Colin W. Hoy

• Sheila C. Steiner

• Robert T. Knight

Date: 2020

DOI: https://doi.org/10.1101/2020.10.20.347740

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Top–Down Attentional Modulation in Human Frontal Cortex: Differential Engagement during External and Internal Attention

Abstract:

Decades of electrophysiological research on top–down control converge on the role of the lateral frontal cortex in facilitating attention to behaviorally relevant external inputs. However, the involvement of frontal cortex in the top–down control of attention directed to the external versus internal environment remains poorly understood. To address this, we recorded intracranial electrocorticography while subjects directed their attention externally to tones and responded to infrequent target tones, or internally to their own thoughts while ignoring the tones. Our analyses focused on frontal and temporal cortices. We first computed the target effect, as indexed by the difference in high frequency activity (70–150 Hz) between target and standard tones. Importantly, we then compared the target effect between external and internal attention, reflecting a top–down attentional effect elicited by task demands, in each region of interest. Both frontal and temporal cortices showed target effects during external and internal attention, suggesting this effect is present irrespective of attention states. However, only the frontal cortex showed an enhanced target effect during external relative to internal attention. These findings provide electrophysiological evidence for top–down attentional modulation in the lateral frontal cortex, revealing preferential engagement with external attention.

Authors:

• Julia WY Kam

• Randolph F Helfrich

• Anne-Kristin Solbakk

• Tor Endestad

• Pål G Larsson

• Jack J Lin

• Robert T Knight

Date: 2020

DOI: https://doi.org/10.1093/cercor/bhaa262

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Insights into human cognition from intracranial EEG: A review of audition, memory, internal cognition, and causality

Abstract:

By recording neural activity directly from the human brain, researchers gain unprecedented insight into how neurocognitive processes unfold in real time. We first briefly discuss how intracranial electroencephalography (iEEG) recordings, performed for clinical practice, are used to study human cognition with the spatiotemporal and single-trial precision traditionally limited to non-human animal research. We then delineate how studies using iEEG have informed our understanding of issues fundamental to human cognition: auditory prediction, working and episodic memory, and internal cognition. We also discuss the potential of iEEG to infer causality through the manipulation or ‘engineering’ of neurocognitive processes via spatiotemporally precise electrical stimulation. We close by highlighting limitations of iEEG, potential of burgeoning techniques to further increase spatiotemporal precision, and implications for future research using intracranial approaches to understand, restore, and enhance human cognition.

Authors:

• Elizabeth Johnson

• Julia WY Kam

• Athina Tzovara

• Robert T Knight

Date: 2020

DOI: https://dx.doi.org/10.1088%2F1741-2552%2Fabb7a5

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Dissociation of broadband high-frequency activity and neuronal firing in the neocortex

Abstract:

Broadband high-frequency activity (BHA; 70 to 150 Hz), also known as “high gamma,” a key analytic signal in human intracranial (electrocorticographic) recordings, is often assumed to reflect local neural firing [multiunit activity (MUA)]. As the precise physiological substrates of BHA are unknown, this assumption remains controversial. Our analysis of laminar multielectrode data from V1 and A1 in monkeys outlines two components of stimulus-evoked BHA distributed across the cortical layers: an “early-deep” and “late-superficial” response. Early-deep BHA has a clear spatial and temporal overlap with MUA. Late-superficial BHA was more prominent and accounted for more of the BHA signal measured near the cortical pial surface. However, its association with local MUA is weak and often undetectable, consistent with the view that it reflects dendritic processes separable from local neuronal firing.

Authors:

• Marcin Leszczyński

• Annamaria Barczak

• Yoshinao Kajikawa

• Istvan Ulbert

• Arnaud Y Falchier

• Idan Tal

• Saskia Haegens

• Lucia Melloni

• Robert T Knight

• Charles E Schroeder

Date: 2020

DOI: 10.1126/sciadv.abb0977

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An electrophysiological marker of arousal level in humans

Abstract:

Deep non-rapid eye movement sleep (NREM) and general anesthesia with propofol are prominent states of reduced arousal linked to the occurrence of synchronized oscillations in the electroencephalogram (EEG). Although rapid eye movement (REM) sleep is also associated with diminished arousal levels, it is characterized by a desynchronized, ‘wake-like’ EEG. This observation implies that reduced arousal states are not necessarily only defined by synchronous oscillatory activity. Using intracranial and surface EEG recordings in four independent data sets, we demonstrate that the 1/f spectral slope of the electrophysiological power spectrum, which reflects the non-oscillatory, scale-free component of neural activity, delineates wakefulness from propofol anesthesia, NREM and REM sleep. Critically, the spectral slope discriminates wakefulness from REM sleep solely based on the neurophysiological brain state. Taken together, our findings describe a common electrophysiological marker that tracks states of reduced arousal, including different sleep stages as well as anesthesia in humans.

Authors:

• Janna D Lendner

• Randolph F Helfrich

• Bryce A Mander

• Luis Romundstad

• Jack J Lin

• Matthew P Walker

• Pal G Larsson

• Robert T Knight

Date: 2020

DOI: https://doi.org/10.7554/eLife.55092

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Language Neuroplasticity in Brain Tumor Patients Revealed by Magnetoencephalography

Abstract:

Little is known about language impairment in brain tumor patients, especially in the presurgical phase. Impairment in this population may be missed because standardized tests fail to capture mild deficits. Additionally, neuroplasticity may also contribute to minimizing language impairments. We examined 14 presurgical patients with brain tumors in the language-dominant hemisphere using magnetoencephalography (MEG) while they performed a demanding picture–word interference task, that is, participants name pictures while ignoring distractor words. Brain tumor patients had behavioral picture-naming effects typically observed in healthy controls. The MEG responses also showed the expected pattern in its timing and amplitude modulation typical of controls, but with an altered spatial distribution of right hemisphere sources, in contrast to the classic left hemisphere source found in healthy individuals. This finding supports tumor-induced neural reorganization of language before surgery. Crucially, the use of electrophysiology allowed us to show the “same” neuronal response in terms of its timing and amplitude modulation in the right hemisphere, supporting the hypothesis that the processes performed by the right hemisphere following reorganization are similar in nature to those (previously) performed by the left hemisphere. We also identified one participant with a fast-growing tumor affecting large parts of critical language areas and underlying ventral and dorsal white matter tracts who showed a deviant pattern in behavior and in the MEG event-related responses. In conclusion, our results attest to the validity of using a demanding picture-naming task in presurgical patients and provide evidence for neuroplasticity, with the right hemisphere performing similar computations as the left hemisphere typically performs.

Authors:

• Vitória Piai

• Elke De Witte

• Joanna Sierpowska

• Xiaochen Zheng

• Leighton B Hinkley

• Danielle Mizuiri

• Robert T Knight

• Mitchel S Berger

• Srikantan S Nagarajan

Date: 2020

DOI: https://doi.org/10.1162/jocn_a_01561

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Coupling between slow-waves and sharp-wave ripples organizes distributed neural activity during sleep in humans

Abstract:

Hippocampal-dependent memory consolidation during sleep is hypothesized to depend on the synchronization of distributed neuronal ensembles, organized by the hippocampal sharp-wave ripples (SWRs, 80-150 Hz) and subcortical/cortical slow-waves (0.5-4 Hz). However, the precise role of SWR-slow-wave interactions in synchronizing subcortical/cortical neuronal activity is unclear. Here, we leverage intracranial electrophysiological recordings from the human hippocampus, amygdala, temporal and frontal cortices, to examine activity modulation and cross-regional coordination during SWRs. Hippocampal SWRs are associated with widespread modulation of high frequency activity (HFA; 70-200 Hz) a measure of local neuronal activation. This peri-SWR HFA modulation is predicted by the coupling between hippocampal SWRs and local subcortical/cortical slow-waves. Finally, local cortical slow-wave phase offsets during SWRs predicted functional connectivity between the frontal and temporal cortex. These findings suggest a selection mechanism wherein hippocampal SWR and cortical slow-wave synchronization governs the transient engagement of distributed neuronal populations supporting hippocampal-dependent memory consolidation.

Authors:

• Ivan Skelin

• Haoxin Zhang

• Jie Zheng

• Shiting Ma

• Bryce A Mander

• Olivia Kim Mcmanus

• Sumeet Vadera

• Robert T Knight

• Bruce L McNaughton

• Jack J Lin

Date: 2020

DOI: https://doi.org/10.1101/2020.05.24.113480

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Behavioral and EEG Measures Show no Amplifying Effects of Shared Attention on Attention or Memory

Abstract:

Shared attention experiments examine the potential differences in function or behavior when stimuli are experienced alone or in the presence of others, and when simultaneous attention of the participants to the same stimulus or set is involved. Previous work has found enhanced reactions to emotional stimuli in social situations, yet these changes might represent enhanced communicative or motivational purposes. This study examines whether viewing emotional stimuli in the presence of another person influences attention to or memory for the stimulus. Participants passively viewed emotionally-valenced stimuli while completing another task (counting flowers). Each participant performed this task both alone and in a shared attention condition (simultaneously with another person in the same room) while EEG signals were measured. Recognition of the emotional pictures was later measured. A significant shared attention behavioral effect was found in the attention task but not in the recognition task. Compared to event-related potential responses for neutral pictures, we found higher P3b response for task relevant stimuli (flowers), and higher Late Positive Potential (LPP) responses for emotional stimuli. However, no main effect was found for shared attention between presence conditions. To conclude, shared attention may therefore have a more limited effect on cognitive processes than previously suggested.

Authors:

• Noam Mairon

• Mor Nahum

• Arjen Stolk

• Robert T Knight

• Anat Perry

Date: 2020

DOI: 10.1038/s41598-020-65311-7

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The brain tracks auditory rhythm predictability independent of selective attention

Abstract:

The brain responds to violations of expected rhythms, due to extraction- and prediction of the temporal structure in auditory input. Yet, it is unknown how probability of rhythm violations affects the overall rhythm predictability. Another unresolved question is whether predictive processes are independent of attention processes. In this study, EEG was recorded while subjects listened to rhythmic sequences. Predictability was manipulated by changing the stimulus-onset-asynchrony (SOA deviants) for given tones in the rhythm. When SOA deviants were inserted rarely, predictability remained high, whereas predictability was lower with more frequent SOA deviants. Dichotic tone-presentation allowed for independent manipulation of attention, as specific tones of the rhythm were presented to separate ears. Attention was manipulated by instructing subjects to attend to tones in one ear only, while keeping the rhythmic structure of tones constant. The analyses of event-related potentials revealed an attenuated N1 for tones when rhythm predictability was high, while the N1 was enhanced by attention to tones. Bayesian statistics revealed no interaction between predictability and attention. A right-lateralization of attention effects, but not predictability effects, suggested potentially different cortical processes. This is the first study to show that probability of rhythm violation influences rhythm predictability, independent of attention.

Authors:

• Maja D Foldal

• Alejandro O Blenkmann

• Anaïs Llorens

• Robert T Knight

• Anne-Kristin Solbakk

• Tor Endestad

Date: 2020

DOI: https://doi.org/10.1038/s41598-020-64758-y

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Using Coherence-based spectro-spatial filters for stimulus features prediction from electro-corticographic recordings

Abstract:

The traditional approach in neuroscience relies on encoding models where brain responses are related to different stimuli in order to establish dependencies. In decoding tasks, on the contrary, brain responses are used to predict the stimuli, and traditionally, the signals are assumed stationary within trials, which is rarely the case for natural stimuli. We hypothesize that a decoding model assuming each experimental trial as a realization of a random process more likely reflects the statistical properties of the undergoing process compared to the assumption of stationarity. Here, we propose a Coherence-based spectro-spatial filter that allows for reconstructing stimulus features from brain signal’s features. The proposed method extracts common patterns between features of the brain signals and the stimuli that produced them. These patterns, originating from different recording electrodes are combined, forming a spatial filter that produces a unified prediction of the presented stimulus. This approach takes into account frequency, phase, and spatial distribution of brain features, hence avoiding the need to predefine specific frequency bands of interest or phase relationships between stimulus and brain responses manually. Furthermore, the model does not require the tuning of hyper-parameters, reducing significantly the computational load attached to it. Using three different cognitive tasks (motor movements, speech perception, and speech production), we show that the proposed method consistently improves stimulus feature predictions in terms of correlation (group averages of 0.74 for motor movements, 0.84 for speech perception, and 0.74 for speech production) in comparison with other methods based on regularized multivariate regression, probabilistic graphical models and artificial neural networks. Furthermore, the model parameters revealed those anatomical regions and spectral components that were discriminant in the different cognitive tasks. This novel method does not only provide a useful tool to address fundamental neuroscience questions, but could also be applied to neuroprosthetics.

Authors:

• Jaime Delgado Saa

• Andy Christen

• Stephanie Martin

• Brian N Pasley

• Robert T Knight

• Anne-Lise Giraud

Date: 2020

DOI: https://doi.org/10.1038/s41598-020-63303-1

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Comparison between a wireless dry electrode EEG system with a conventional wired wet electrode EEG system for clinical applications

Abstract:

Dry electrode electroencephalogram (EEG) recording combined with wireless data transmission offers an alternative tool to conventional wet electrode EEG systems. However, the question remains whether the signal quality of dry electrode recordings is comparable to wet electrode recordings in the clinical context. We recorded the resting state EEG (rsEEG), the visual evoked potentials (VEP) and the visual P300 (P3) from 16 healthy subjects (age range: 26–79 years) and 16 neurological patients who reported subjective memory impairment (age range: 50–83 years). Each subject took part in two recordings on different days, one with 19 dry electrodes and another with 19 wet electrodes. They reported their preferred EEG system. Comparisons of the rsEEG recordings were conducted qualitatively by independent visual evaluation by two neurologists blinded to the EEG system used and quantitatively by spectral analysis of the rsEEG. The P100 visual evoked potential (VEP) and P3 event-related potential (ERP) were compared in terms of latency, amplitude and pre-stimulus noise. The majority of subjects preferred the dry electrode headset. Both neurologists reported that all rsEEG traces were comparable between the wet and dry electrode headsets. Absolute Alpha and Beta power during rest did not statistically differ between the two EEG systems (p > 0.05 in all cases). However, Theta and Delta power was slightly higher with the dry electrodes (p = 0.0004 for Theta and p < 0.0001 for Delta). For ERPs, the mean latencies and amplitudes of the P100 VEP and P3 ERP showed comparable values (p > 0.10 in all cases) with a similar spatial distribution for both wet and dry electrode systems. These results suggest that the signal quality, ease of set-up and portability of the dry electrode EEG headset used in our study comply with the needs of clinical applications.

Authors:

• Hermann Hinrichs

• Michael Scholz

• Anne Katrin Baum

• Julia WY Kam

• Robert T Knight

• Hans-Jochen Heinze

Date: 2020

DOI: https://doi.org/10.1038/s41598-020-62154-0

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Slow wave-spindle coupling during sleep predicts language learning and associated oscillatory activity

Abstract:

Language is one of the most defining human capabilities, involving the coordination of brain networks that generalise the meaning of linguistic units of varying complexity. On a neural level, neocortical slow waves and thalamic spindles during sleep facilitate the reactivation of newly encoded memory traces, manifesting in distinct oscillatory activity during retrieval. However, it is currently unknown if the effect of sleep on memory extends to the generalisation of the mechanisms that subserve sentence comprehension. We address this question by analysing electroencephalogram data recorded from 36 participants during an artificial language learning task and an 8hr nocturnal sleep period. We found that a period of sleep was associated with increased alpha/beta synchronisation and improved behavioural performance. Cross-frequency coupling analyses also revealed that spindle-slow wave coupling predicted the consolidation of varying word order permutations, which was associated with distinct patterns of task-related oscillatory activity during sentence processing. Taken together, this study presents converging behavioural and neurophysiological evidence for a role of sleep in the consolidation of higher order language learning and associated oscillatory neuronal activity.

Authors:

• Zachariah R Cross

• Randolph F Helfrich

• Mark J Kohler

• Andrew W Corcoran

• Scott Coussens

• Lena Zou-Williams

• Matthias Schlesewsky

• M Gareth Gaskell

• Robert T Knight

• Ina Bornkessel-Schlesewsky

Date: 2020

DOI: https://doi.org/10.1101/2020.02.13.948539

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Subcortical Intermittent Theta-Burst Stimulation (iTBS) Increases Theta-Power in Dorsolateral Prefrontal Cortex (DLPFC)

Introduction:

Cognitive symptoms from Parkinson’s disease cause severe disability and significantly limit quality of life. Little is known about mechanisms of cognitive impairment in PD, although aberrant oscillatory activity in basal ganglia-thalamo-prefrontal cortical circuits likely plays an important role. While continuous high-frequency deep brain stimulation (DBS) improves motor symptoms, it is generally ineffective for cognitive symptoms. Although we lack robust treatment options for these symptoms, recent studies with transcranial magnetic stimulation (TMS), applying intermittent theta-burst stimulation (iTBS) to dorsolateral prefrontal cortex (DLPFC), suggest beneficial effects for certain aspects of cognition, such as memory or inhibitory control. While TMS is non-invasive, its results are transient and require repeated application. Subcortical DBS targets have strong reciprocal connections with prefrontal cortex, such that iTBS through the permanently implanted lead might represent a more durable solution. Here we demonstrate safety and feasibility for delivering iTBS from the DBS electrode and explore changes in DLPFC electrophysiology.

Authors:

• J Nicole Bentley

• Zachary T Irwin

• Sarah D Black

• Megan L Roach

• Ryan J Vaden

• Christopher L Gonzalez

• Anas U Khan

• Galal A El-Sayed

• Robert T Knight

• Barton L Guthrie

• Harrison C Walker

Date: 2020

DOI: https://doi.org/10.3389/fnins.2020.00041

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Preservation of Interference Effects in Working Memory After Orbitofrontal Damage

Abstract:

Orbitofrontal cortex (OFC) is implicated in multiple cognitive processes, including inhibitory control, context memory, recency judgment, and choice behavior. Despite an emerging understanding of the role of OFC in memory and executive control, its necessity for core working memory (WM) operations remains undefined. Here, we assessed the impact of OFC damage on interference effects in WM using a Recent Probes task based on the Sternberg item-recognition task (1966). Subjects were asked to memorize a set of letters and then indicate whether a probe letter was presented in a particular set. Four conditions were created according to the forthcoming response (“yes”/“no”) and the recency of the probe (presented in the previous trial set or not). We compared behavioral and electroencephalography (EEG) responses between healthy subjects (n = 14) and patients with bilateral OFC damage (n = 14). Both groups had the same recency pattern of slower reaction time (RT) when the probe was presented in the previous trial but not in the current one, reflecting the proactive interference (PI). The within-group electrophysiological results showed no condition difference during letter encoding and maintenance. In contrast, event-related potentials (ERPs) to probes showed distinct within-group condition effects, and condition by group effects. The response and recency effects for controls occurred within the same time window (300–500 ms after probe onset) and were observed in two distinct spatial groups including right centro-posterior and left frontal electrodes. Both clusters showed ERP differences elicited by the response effect, and one cluster was also sensitive to the recency manipulation. Condition differences for the OFC group involved two different clusters, encompassing only left hemisphere electrodes and occurring during two consecutive time windows (345–463 ms and 565–710 ms). Both clusters were sensitive to the response effect, but no recency effect was found despite the behavioral recency effect. Although the groups had different electrophysiological responses, the maintenance of letters in WM, the evaluation of the context of the probe, and the decision to accept or reject a probed letter were preserved in OFC patients. The results suggest that neural reorganization may contribute to intact recency judgment and response after OFC damage.

Authors:

• Anaïs Llorens

• Ingrid Funderud

• Alejandro O Blenkmann

• James Lubell

• Maja Foldal

• Sabine Leske

• Rene Huster

• Torstein R Meling

• Robert T Knight

• Anne-Kristin Solbakk

• Tor Endestad

Date: 2020

DOI: https://doi.org/10.3389/fnhum.2019.00445

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