Ongoing Neural Processes Research Articles

Cellular computation and cognition.

Contemporary neural network models often overlook a central biological fact about neural processing: that single neurons are themselves complex, semi-autonomous computing systems. Both the information processing and information storage abilities of actual biological neurons vastly exceed the simple weighted sum of synaptic inputs computed by the "units" in standard neural network models. Neurons are eukaryotic cells that store information not only in synapses, but also in their dendritic structure and connectivity, as well as genetic "marking" in the epigenome of each individual cell. Each neuron computes a complex nonlinear function of its inputs, roughly equivalent in processing capacity to an entire 1990s-era neural network model. Furthermore, individual cells provide the biological interface between gene expression, ongoing neural processing, and stored long-term memory traces. Neurons in all organisms have these properties, which are thus relevant to all of neuroscience and cognitive biology. Single-cell computation may also play a particular role in explaining some unusual features of human cognition. The recognition of the centrality of cellular computation to "natural computation" in brains, and of the constraints it imposes upon brain evolution, thus has important implications for the evolution of cognition, and how we study it.

EEG-Microstates Reflect Auditory Distraction After Attentive Audiovisual Perception Recruitment of Cognitive Control Networks.

Processing of sensory information is embedded into ongoing neural processes which contribute to brain states. Electroencephalographic microstates are semi-stable short-lived power distributions which have been associated with subsystem activity such as auditory, visual and attention networks. Here we explore changes in electrical brain states in response to an audiovisual perception and memorization task under conditions of auditory distraction. We discovered changes in brain microstates reflecting a weakening of states representing activity of the auditory system and strengthening of salience networks, supporting the idea that salience networks are active after audiovisual encoding and during memorization to protect memories and concentrate on upcoming behavioural response.

State-related neural influences on fMRI connectivity estimation

The spatiotemporal structure of functional magnetic resonance imaging (fMRI) signals has provided a valuable window into the network underpinnings of human brain function and dysfunction. Although some cross-regional temporal correlation patterns (functional connectivity; FC) exhibit a high degree of stability across individuals and species, there is growing acknowledgment that measures of FC can exhibit marked changes over a range of temporal scales. Further, FC can co-vary with experimental task demands and ongoing neural processes linked to arousal, consciousness and perception, cognitive and affective state, and brain-body interactions. The increased recognition that such interrelated neural processes modulate FC measurements has raised both challenges and new opportunities in using FC to investigate brain function. Here, we review recent advances in the quantification of neural effects that shape fMRI FC and discuss the broad implications of these findings in the design and analysis of fMRI studies. We also discuss how a more complete understanding of the neural factors that shape FC measurements can resolve apparent inconsistencies in the literature and lead to more interpretable conclusions from fMRI studies.

Tensor decompositions and data fusion in epileptic electroencephalography and functional magnetic resonance imaging data

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) record a mixture of ongoing neural processes, physiological and nonphysiological noise. The pattern of interest, such as epileptic activity, is often hidden within this noisy mixture. Therefore, blind source separation (BSS) techniques, which can retrieve the activity pattern of each underlying source, are very useful. Tensor decomposition techniques are very well suited to solve the BSS problem, as they provide a unique solution under mild constraints. Uniqueness is crucial for an unambiguous interpretation of the components, matching them to true neural processes and characterizing them using the component signatures. Moreover, tensors provide a natural representation of the inherently multidimensional EEG and fMRI, and preserve the structural information defined by the interdependencies among the various modes such as channels, time, patients, etc. Despite the well‐developed theoretical framework, tensor‐based analysis of real, large‐scale clinical datasets is still scarce. Indeed, the application of tensor methods is not straightforward. Finding an appropriate tensor representation, suitable tensor model, and interpretation are application dependent choices, which require expertise both in neuroscience and in multilinear algebra. The aim of this paper is to provide a general guideline for these choices and illustrate them through successful applications in epilepsy. WIREs Data Mining Knowl Discov 2017, 7:e1197. doi: 10.1002/widm.1197This article is categorized under: Algorithmic Development > Biological Data Mining Algorithmic Development > Spatial and Temporal Data Mining Algorithmic Development > Structure Discovery

Improving spatial localization in MEG inverse imaging by leveraging intersubject anatomical differences.

Modern neuroimaging techniques enable non-invasive observation of ongoing neural processing, with magnetoencephalography (MEG) in particular providing direct measurement of neural activity with millisecond time resolution. However, accurately mapping measured MEG sensor readings onto the underlying source neural structures remains an active area of research. This so-called “inverse problem” is ill posed, and poses a challenge for source estimation that is often cited as a drawback limiting MEG data interpretation. However, anatomically constrained MEG localization estimates may be more accurate than commonly believed. Here we hypothesize that, by combining anatomically constrained inverse estimates across subjects, the spatial uncertainty of MEG source localization can be mitigated. Specifically, we argue that differences in subject brain geometry yield differences in point-spread functions, resulting in improved spatial localization across subjects. To test this, we use standard methods to combine subject anatomical MRI scans with coregistration information to obtain an accurate forward (physical) solution, modeling the MEG sensor data resulting from brain activity originating from different cortical locations. Using a linear minimum-norm inverse to localize this brain activity, we demonstrate that a substantial increase in the spatial accuracy of MEG source localization can result from combining data from subjects with differing brain geometry. This improvement may be enabled by an increase in the amount of available spatial information in MEG data as measurements from different subjects are combined. This approach becomes more important in the face of practical issues of coregistration errors and potential noise sources, where we observe even larger improvements in localization when combining data across subjects. Finally, we use a simple auditory N100(m) localization task to show how this effect can influence localization using a recorded neural dataset.

The ongoing cognitive processing of exclusionary social events: Evidence from event-related potentials

Exclusionary social events are known to cause alterations in neural activity and attention-related processes. However, the precise nature of these neural adjustments remains unknown as previous research has been limited to examining social interactions and exclusionary events as unitary phenomena. To address this limitation, we assessed neural activity during both inclusionary and exclusionary social interactions by examining event-related brain potentials at multiple points within each social event. Our results show an initial enhancement of anterior cingulate cortex -related activation, indexed by the anterior N2, in response to specific exclusionary events followed by an enhanced attentional orienting response, indexed by the P3a, to later segments of each exclusionary event. Decreases in this P3a activation from social inclusion to social exclusion were associated with self-reported increases in anxiety, negative affect, and feelings of depression from inclusion to exclusion. Together, these findings provide novel insights into the dynamic and ongoing neural processes associated with attentional allocation toward social exclusion and the nature of the relationships between neural and behavioral reactions to exclusionary social interactions.

P 64. Cartography of causal contributions of human frontal cortex to visual attention

It is widely known that the human frontal cortex is involved in the allocation of visual attention, however, the exact causal functional contributions of individual subregions are not well understood. In the present study, we used a simple visual localization task and applied rTMS pulses to map frontal cortical subregions likely to generate significant visuo-spatial biases during the spatial deployment of attention prior to perception. A group of nine adult healthy subjects executed a task based on the localization of small rectangular black dots. Targets were displayed unilaterally (left or right) or bilaterally (left and right) for a brief period (40 ms). In a systematic mapping approach, a stimulation grid of 9 (3 × 3) sites was anchored 2 cm rostral to the motor hand area. Three pulses of real or sham 10 Hz rTMS were delivered in a counterbalanced manner, at each of the grid locations 50 ms post target onset to interfere with the ongoing neural processing. As a main finding, significant deterioration of detection performance, as measured by effective reaction time, for stimuli in the contralateral hemifield and increased performance for ipsilateral targets were observed for two grid regions anatomically associated with the right FEF and right middle frontal gyrus. We conclude that the disruptive effects of TMS on a simple spatial localization task for which a well-balanced deployment of attention is required are exquisitely spatially selective, and are found in specific frontal cortical subregions.

The Temporal Dynamics of Early Visual Cortex Involvement in Behavioral Priming

Transcranial magnetic stimulation (TMS) allows for non-invasive interference with ongoing neural processing. Applied in a chronometric design over early visual cortex (EVC), TMS has proved valuable in indicating at which particular time point EVC must remain unperturbed for (conscious) vision to be established. In the current study, we set out to examine the effect of EVC TMS across a broad range of time points, both before (pre-stimulus) and after (post-stimulus) the onset of symbolic visual stimuli. Behavioral priming studies have shown that the behavioral impact of a visual stimulus can be independent from its conscious perception, suggesting two independent neural signatures. To assess whether TMS-induced suppression of visual awareness can be dissociated from behavioral priming in the temporal domain, we thus implemented three different measures of visual processing, namely performance on a standard visual discrimination task, a subjective rating of stimulus visibility, and a visual priming task. To control for non-neural TMS effects, we performed electrooculographical recordings, placebo TMS (sham), and control site TMS (vertex). Our results suggest that, when considering the appropriate control data, the temporal pattern of EVC TMS disruption on visual discrimination, subjective awareness and behavioral priming are not dissociable. Instead, TMS to EVC disrupts visual perception holistically, both when applied before and after the onset of a visual stimulus. The current findings are discussed in light of their implications on models of visual awareness and (subliminal) priming.

Measuring Internal Representations from Behavioral and Brain Data

The study of internal knowledge representations is a cornerstone of the research agenda in the interdisciplinary study of cognition. An influential proposal assumes that the brain uses its internal knowledge of the external world to constrain, in a top-down manner, high-dimensional sensory data into a lower-dimensional representation that enables perceptual decisions and other higher-level cognitive functions [1-9]. This proposal relies on a precise formulation of the observer-specific internal knowledge (i.e., the internal representations, or models) that guides reduction of the high-dimensional retinal input onto a low-dimensional code. Here, we directly revealed the content of subjective internal representations by instructing five observers to detect a face in the presence of only white noise, to force a pure top-down, knowledge-based task. We used reverse correlation methods to visualize each observer's internal representation that supports detection of an illusory face. Using reverse correlation again, this time applied to observers' electroencephalogram activity, we established where and when in the brain specific internal knowledge conceptually interprets the input white noise as a face. We show that internal representations can be reconstructed experimentally from behavioral and brain data, and that their content drives neural activity first over frontal and then over occipitotemporal cortex.

Prestimulus theta activity predicts correct source memory retrieval.

Recent evidence indicates that the processing of a stimulus can be influenced by preceding patterns of brain activity. Here we examine whether prestimulus oscillatory brain activity can influence the ability to retrieve episodic memories. Neural activity in the theta-frequency band (4-8 Hz) was enhanced before presentation of test items which elicited accurate recollection of contextual details of the prior study episode ("source retrieval"), relative to trials for which item recognition was successful but source retrieval failed. Poststimulus theta activity was also related to source retrieval, and the magnitude of poststimulus theta was predicted by the magnitude of the prestimulus theta effects. The results suggest that ongoing neural processes occurring before stimulus onset might play a critical role in readying the brain for successful memory retrieval.

The Functional Effect of Transcranial Magnetic Stimulation: Signal Suppression or Neural Noise Generation?

Transcranial magnetic stimulation (TMS) is a popular tool for mapping perceptual and cognitive processes in the human brain. It uses a magnetic field to stimulate the brain, modifying ongoing activity in neural tissue under the stimulating coil, producing an effect that has been likened to a "virtual lesion." However, research into the functional basis of this effect, essential for the interpretation of findings, lags behind its application. Acutely, TMS may disable neuronal function, thereby interrupting ongoing neural processes. Alternatively, the effects of TMS have been attributed to an injection of "neural noise," consistent with its immediate and effectively random depolarization of neurons. Here we apply an added-noise paradigm to test these alternatives. We delivered TMS to the visual cortex and measured its effect on a simple visual discrimination task, while concurrently manipulating the level of image noise in the visual stimulus itself. TMS increased thresholds overall; and increasing the amount of image noise systematically increased discrimination thresholds. However, these two effects were not independent. Rather, TMS interacted multiplicatively with the image noise, consistent with a reduction in the strength of the visual signal. Indeed, in this paradigm, there was no evidence that TMS independently added noise to the visual process. Thus, our findings indicate that the "virtual lesion" produced by TMS can take the form of a loss of signal strength which may reflect a momentary interruption to ongoing neural processing.

Brain stimulation for neurological and psychiatric disorders, current status and future direction.

Interest in brain stimulation therapies has been rejuvenated over the last decade and brain stimulation therapy has become an alternative treatment for many neurological and psychiatric disorders, including Parkinson's disease (PD), dystonia, pain, epilepsy, depression, and schizophrenia. The effects of brain stimulation on PD are well described, and this treatment has been widely used for such conditions worldwide. Treatments for other conditions are still in experimental stages and large-scale, well controlled studies are needed to refine the treatment procedures. In the treatment of intractable brain disorders, brain stimulation, especially transcranial magnetic stimulation (TMS), is an attractive alternative to surgical lesioning as it is relatively safe, reversible, and flexible. Brain stimulation, delivered either via deeply implanted electrodes or from a surface-mounted transcranial magnetic device, can alter abnormal neural circuits underlying brain disorders. The neural mechanisms mediating the beneficial effects of brain stimulation, however, are poorly understood. Conflicting theories and experimental data have been presented. It seems that the action of stimulation on brain circuitry is not limited to simple excitation or inhibition. Alterations of neural firing patterns and long-term effects on neurotransmitter and receptor systems may also play important roles in the therapeutic effects of brain stimulation. Future research on both the basic and clinical fronts will deepen our understanding of how brain stimulation works. Real-time computation of neural activity allows for integration of brain stimulation signals into ongoing neural processing. In this way abnormal circuit activity can be adjusted by optimal therapeutic brain stimulation paradigms.

Temporal integration in visual memory.

Iconic memory has often been likened to a sensory store whose contents drain away rapidly as soon as the inducing stimulus is turned off. Instances of short-lived visible persistence have been explained in terms of the decaying contents of iconic store. A fundamental requirement of this storage model is that strength of persistence should be a decreasing function of time elapsed since the cessation--not since the onset--of the inducing stimulation. That is, strength of visible persistence may be directly related--but not inversely related--to the duration of the inducing stimulus. Two complementary paradigms were utilized in the present studies. In the first paradigm performance was facilitated by visible persistence in that the task required the bridging of a temporal gap between two successive displays. In the second paradigm (forward visual masking by pattern), performance was impaired lingering visible persistence of the temporally leading mask. Both paradigms yielded evidence of an inverse relationship between duration of inducing stimulus and duration of visible persistence. More specifically, in a task requiring temporal integration of a pattern displayed briefly in two successive portions, performance was severely impaired if the duration of the leading part exceeded about 100 msec. This suggests an inverse relationship between duration of inducing stimulus and duration of sensory persistence and allows the inference that visual persistence may be identified more fittingly with ongoing neural processes than with the decaying contents of an iconic store. In keeping with this suggestion, two experiments disconfirmed the conjecture that lack of temporal integration following long induced stimuli could be ascribed to emergence of unitary form separately in the two portions of the display or to the triggering of some sort of discontinuity detection mechanism within the visual system. In added support of a "processing" model, two further studies showed that the severity of forward masking by pattern declines sharply as the duration of the leading mask is increased. This pattern of results is equally unsupportive of a storage theory of iconic persistence as a perceptual moment theory in any of its versions. This is so because both theories regard interstimulus interval rather than stimulus-onset asynchrony as the crucial factor in temporal integration. Neither can the results be explained in terms of receptor adaptation or of metacontrast suppression. The theory of inhibitory channel interactions can encompass the more prominent aspects of the results but fails to account for foveal suppression and for some crucial temporal effects.

Temporal characteristics of iconic memory.

THE duration of visual persistence (iconic memory) is inversely related, up to a point, to the duration of the inducing stimulus. This suggests that iconic memory can more properly be identified with ongoing neural processes than with the decaying contents of a sensory store. Since the publication of Sperling's influential monograph1 there has been general agreement that a relatively faithful representation of a visual display remains perceptually available for several hundred milliseconds after the distal stimulus has vanished. This led to the postulation of a short-term visual store, also called iconic memory2 or sensory register3, with contents decaying rapidly after the termination of the inducing display. The terms visual persistence or icon are commonly used to refer to the perceptual availability of the decaying contents of the sensory store. Iconic memory is regarded as having temporal combinatorial properties which allow perceptual integration of two or more sequential displays even if separated by a brief temporal gap. Integration in iconic memory was convincingly demonstrated in a study where the subjects were required to identify which element in a briefly-displayed array of 16 alphabet characters had been singled out by a temporally trailing bar marker4. Temporal integration has also provided an explanation for some aspects of visual masking5 and for temporal integration of patterns whose parts were presented sequentially in time6,7. Here I question the view that iconic memory is a store whose contents begin to decay when the inducing stimulus is terminated. I suggest that the duration of iconic persistence is linked to the duration of visual processes which begin at the onset of stimulation and continue for a given duration, whether or not the inducing stimulus is still on display. This view is based on the finding that the duration of visual persistence is negatively related to the duration of the inducing stimulus.