Biology subjects

Knight, R. T.

Publications and source records attributed to Knight, R. T..

11 recordsLinked to original sources

bioRxiv2018

Human posterior parietal cortex responds to visual stimuli as early as peristriate occipital cortex

Much of what is known about the timing of visual processing in the brain is inferred from intracranial studies in monkeys, with human data limited to mainly non-invasive methods with lower spatial resolution. Here, we estimated visual onset latencies from electrocorticographic (ECoG) recordings in a patient who was implanted with 112 sub-dural electrodes, distributed across the posterior cortex of the right hemisphere, for pre-surgical evaluation of intractable epilepsy. Functional MRI prior to surgery was used to determine boundaries of visual areas. The patient was presented with images of objects from several categories. Event Related Potentials (ERPs) were calculated across all categories excluding targets, and statistically reliable onset latencies were determined using a bootstrapping procedure over the single trial baseline activity in individual electrodes. The distribution of onset latencies broadly reflected the known hierarchy of visual areas, with the earliest cortical responses in primary visual cortex, and higher areas showing later responses. A clear exception to this pattern was robust, statistically reliable and spatially localized, very early responses on the bank of the posterior intra-parietal sulcus (IPS). The response in the IPS started nearly simultaneously with responses detected in peristriate visual areas, around 60 milliseconds post-stimulus onset. Our results support the notion of early visual processing in the posterior parietal lobe, not respecting traditional hierarchies, and give direct evidence for the upper limit of onset times of visual responses across the human cortex.

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bioRxiv2018

Direct evidence for prediction signals in frontal cortex independent of prediction error

Predictive coding (PC) has been suggested as one of the main mechanisms used by brains to interact with complex environments. PC theories posit top-down prediction signals, which are compared with actual outcomes, yielding in turn prediction-error signals, which are used, bottom-up, to modify the ensuing predictions. However, disentangling prediction from prediction-error signals has been challenging. Critically, while many studies found indirect evidence for predictive coding in the form of prediction-error signals, direct evidence for the prediction signal is mostly lacking. Here we provide clear evidence, obtained from intracranial cortical recordings in human surgical patients, that the human lateral prefrontal cortex generates prediction signals while anticipating an event. Patients listened to task-irrelevant sequences of repetitive tones including infrequent predictable or unpredictable pitch deviants. The amplitude of high frequency broadband (HFB) neural activity was decreased prior to the onset of expected relative to unexpected deviants in the frontal cortex only, and its amplitude was sensitive to the increasing likelihood of deviants following longer trains of standards in the unpredictable condition. Single trial HFB amplitudes predicted deviations and correlated with post-stimulus response to deviations. These results provide direct evidence for frontal cortex prediction signals independent of prediction-error signals.

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bioRxiv2018

Differential contributions of subthalamic beta rhythms and neural noise to Parkinson motor symptoms

BackgroundExcessive beta oscillatory activity in the subthalamic nucleus (STN) is linked to Parkinsons disease and associated motor symptoms. However, the relationship between beta activity and motor symptoms has been inconsistent, which may influence the efficacy of closed-loop deep brain stimulation.\n\nHypothesisWe hypothesized that this variability is due to the degree of neural noise in STN recordings. Recent evidence has shown that neural noise is influenced by multiple factors, such as development, aging and disease, and could confound measures of beta activity. In this work, we propose a model that disentangles beta oscillatory activity and neural noise in the STN power spectrum.\n\nMethodsWe investigated the impact of neural noise on estimations of beta activity and motor symptoms from data recorded bilaterally from the subthalamic nuclei of thirteen Parkinsonian patients.\n\nResultsResults showed that the relationship between beta oscillatory amplitude and motor symptoms (bradykinesia and rigidity) significantly improved when neural noise was removed from the estimation of beta activity.\n\nConclusionThese findings emphasize the importance of modeling neural components independently for understanding physiological processes associated with Parkinsons disease, and identifying better biomarkers for characterizing symptom severity. Subsequently, we predict that our findings can have a direct application for closed-loop deep brain stimulation on Parkinsons Disease.

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bioRxiv2018

Parameterizing neural power spectra

Electrophysiological signals across species and recording scales exhibit both periodic and aperiodic features. Periodic oscillations have been widely studied and linked to numerous physiological, cognitive, behavioral, and disease states, while the aperiodic \"background\" 1/f component of neural power spectra has received far less attention. Most analyses of oscillations are conducted on a priori, canonically-defined frequency bands without consideration of the underlying aperiodic structure, or verification that a periodic signal even exists in addition to the aperiodic signal. This is problematic, as recent evidence shows that the aperiodic signal is dynamic, changing with age, task demands, and cognitive state. It has also been linked to the relative excitation/inhibition of the underlying neuronal population. This means that standard analytic approaches easily conflate changes in the periodic and aperiodic signals with one another because the aperiodic parameters--along with oscillation center frequency, power, and bandwidth--are all dynamic in physiologically meaningful, but likely different, ways. In order to overcome the limitations of traditional narrowband analyses and to reduce the potentially deleterious effects of conflating these features, we introduce a novel algorithm for automatic parameterization of neural power spectral densities (PSDs) as a combination of the aperiodic signal and putative periodic oscillations. Notably, this algorithm requires no a priori specification of band limits and accounts for potentially-overlapping oscillations while minimizing the degree to which they are confounded with one another. This algorithm is amenable to large-scale data exploration and analysis, providing researchers with a tool to quickly and accurately parameterize neural power spectra.

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bioRxiv2018

Orbitofrontal cortex, dorsolateral prefrontal cortex, and hippocampus represent the magnitude of event saliency

Two primary functions attributed to the hippocampus and prefrontal cortex network are retaining the temporal and spatial associations of events and detecting deviant events. It is, however, unclear how these two functions converge onto one mechanism. Here, we tested whether increased activity with perceiving salient events is a deviant detection signal or contains information about the event associations by reflecting the magnitude of deviance (i.e., event saliency). We also tested how the deviant detection signal is affected by the degree of anticipation. We studied regional neural activity when people watched a movie that had varying saliency of a novel or an anticipated flow of salient events. Using intracranial electroencephalography from ten patients, we observed that high-frequency activity (50-150 Hz) in the hippocampus, dorsolateral prefrontal cortex (dorsolateral PFC), and medial orbitofrontal cortex (OFC) tracked event saliency. We also observed that medial OFC activity was stronger when the salient events were anticipated than when they were novel. These results suggest that dorsolateral PFC and medial OFC, as well as the hippocampus, signify the saliency magnitude of events, reflecting the hierarchical structure of event associations.

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bioRxiv2017

Integrated analysis of anatomical and electrophysiological human intracranial data

The exquisite spatiotemporal precision of human intracranial EEG recordings (iEEG) permits characterizing neural processing with a level of detail that is inaccessible to scalp-EEG, MEG, or fMRI. However, the same qualities that make iEEG an exceptionally powerful tool also present unique challenges. Until now, the fusion of anatomical data (MRI and CT images) with the electrophysiological data and its subsequent analysis has relied on technologically and conceptually challenging combinations of software. Here, we describe a comprehensive protocol that addresses the complexities associated with human iEEG, providing complete transparency and flexibility in the evolution of raw data into illustrative representations. The protocol is directly integrated with an open source toolbox for electrophysiological data analysis (FieldTrip). This allows iEEG researchers to build on a continuously growing body of scriptable and reproducible analysis methods that, over the past decade, have been developed and employed by a large research community. We demonstrate the protocol for an example complex iEEG data set to provide an intuitive and rapid approach to dealing with both neuroanatomical information and large electrophysiological data sets. We explain how the protocol can be largely automated, taking under an hour to complete, and readily adjusted to iEEG data sets with other characteristics.

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bioRxiv2017

Evidence for a causal link between left posterior alpha-beta power decreases and context-driven word production.

Different frequency bands in the electroencephalogram are postulated to support distinct language functions. Studies have suggested that alpha-beta power decreases may index word-retrieval processes. In context-driven word retrieval, participants hear lead-in sentences that either constrain the final word (\"He locked the door with the\") or not (\"She walked in here with the\"). The last word is shown as a picture to be named. Previous studies have consistently found alpha-beta power decreases prior to picture onset for constrained relative to unconstrained sentences, localised to the left lateral-temporal and lateral-frontal lobes. However, the relative contribution of temporal versus frontal areas to alpha-beta power decreases is unknown. We recorded the electroencephalogram from patients with stroke lesions encompassing the left-lateral temporal and inferior parietal regions or left-lateral frontal lobe and from matched controls. Individual-participant analyses revealed a behavioural sentence context facilitation effect in all participants, except for in the two patients with extensive lesions to temporal and inferior-parietal lobes. We replicated the alpha-beta power decreases prior to picture onset in all participants, except for in the two same patients with extensive posterior lesions. Thus, whereas posterior lesions eliminated the behavioural and oscillatory context effect, frontal lesions did not. Hierarchical clustering analyses of the patients lesion profiles, and behavioural and electrophysiological effects identified P7 and P9 as having a unique combination of lesion distribution and context effects. These results indicate a critical role for the left lateral-temporal and inferior parietal lobes, but not frontal cortex, in generating the alpha-beta power decreases underlying context-driven word production.

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bioRxiv2017

Should A Few Null Findings Falsify Prefrontal Theories Of Conscious Perception?

Is activity in prefrontal cortex (PFC) critical for conscious perception? Major theories of consciousness make distinct predictions about the role of PFC, providing an opportunity to arbitrate between these views empirically. Here we address three common misconceptions: i) PFC lesions do not affect subjective perception; ii) PFC activity does not reflect specific perceptual content; iii) PFC involvement in studies of perceptual awareness is solely driven by the need to make reports required by the experimental tasks, rather than subjective experience per se. These claims are incompatible with empirical findings, unless one focuses only on studies using methods with limited sensitivity. The literature highlights PFCs essential role in enabling the subjective experience in perception, contra the objective capacity to perform visual tasks; conflating the two can also be a source of confusion.

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bioRxiv2017

Neural Encoding of Auditory Features during Music Perception and Imagery: Insight into the Brain of a Piano Player

It remains unclear how the human cortex represents spectrotemporal sound features during auditory imagery, and how this representation compares to auditory perception. To assess this, we recorded electrocorticographic signals from an epileptic patient with proficient music ability in two conditions. First, the participant played two piano pieces on an electronic piano with the sound volume of the digital keyboard on. Second, the participant replayed the same piano pieces, but without auditory feedback, and the participant was asked to imagine hearing the music in his mind. In both conditions, the sound output of the keyboard was recorded, thus allowing precise time-locking between the neural activity and the spectrotemporal content of the music imagery. For both conditions, we built encoding models to predict high gamma neural activity (70-150Hz) from the spectrogram representation of the recorded sound. We found robust similarities between perception and imagery - in frequency and temporal tuning properties in auditory areas.\n\nAbbreviations

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bioRxiv2016

Persistent neural activity encoding real-time presence of visual stimuli decays along the ventral stream

Neural populations that encode sensory experience should be persistently active for as long as the experience persists. However, research into visual neural activity has focused almost exclusively on onset-driven responses that cannot account for sustained perception. We used intracranial recordings in humans to determine the degree to which the presence of a visual stimulus is persistently encoded by neural activity. The correspondence between stimulus duration and response duration was strongest in early visual cortex and gradually diminished along the visual hierarchy, such that is was weakest in inferior-temporal category-selective regions. A similar posterior-anterior gradient was found within inferior temporal face-selective regions, with posterior but not anterior sites showing persistent face-selective activity. The results suggest that regions that appear uniform in terms of their category selectivity are dissociated by how they temporally represent a stimulus in support of real-time experience, and delineate a large-scale organizing principle of the ventral visual stream.

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bioRxiv2016

Impaired lexical selection with competing distractors: Evidence from left temporal and left prefrontal lesions

According to the competition account of lexical selection in word production, conceptually driven word retrieval involves the activation of a set of candidate words in left temporal cortex, and competitive selection of the intended word from this set, regulated by frontal cortical mechanisms. However, the relative contribution of these brain regions to competitive lexical selection is uncertain. In the present study, five patients with left prefrontal cortex lesions (overlapping in ventral and dorsal lateral cortex), eight patients with left lateral temporal cortex lesions (overlapping in middle temporal gyrus), and 13 matched controls performed a picture-word interference task. Distractor words were semantically related or unrelated to the picture, or the name of the picture (congruent condition). Semantic interference (related vs unrelated), tapping into competitive lexical selection, was examined. An overall semantic interference effect was observed for the control and left-temporal groups separately. The left-frontal patients did not show a reliable semantic interference effect as a group. The left-temporal patients had increased semantic interference in the error rates relative to controls. Error distribution analyses indicated that these patients had more hesitant responses for the related than for the unrelated condition. We propose that left middle temporal lesions affect the lexical activation component, making lexical selection more susceptible to errors.

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