Exploring the neural basis of cognition: multi-modal links between human fMRI and macaque neurophysiology

Although functional magnetic resonance imaging (fMRI) with sophisticated behavioral paradigms has enabled the investigation of increasingly higher-level cognitive functions in humans, these studies seem to lose touch with neurophysiological studies in macaque monkeys. The application of fMRI and other MRI-based techniques to macaque brains allows studies in the two species to be linked. fMRI in human and macaque subjects using equivalent cognitive tasks enables direct comparisons of the functional brain architecture, even for high-level cognitive functions. Combinations of functional or structural MRI and microelectrode techniques provide ways to explore functional brain networks at multiple spatiotemporal scales. These approaches would illuminate the neurophysiological underpinnings of human cognitive functions by integrating human functional neuroimaging with macaque single-unit recordings.     

Integrating electrophysiology and neuroimaging in the study of human cognition

Noninvasive recordings of electrical and magnetic fields generated by neuronal activity have helped to characterize the temporal sequencing and mechanisms underlying human cognition. Progress is being made toward the goal of localizing the intracranial loci at which many important electromagnetic signals are generated through the use of new analytic techniques and of scalp recordings of electromagnetic activity in neurological patients and through related work in animals. Such methods alone, however, do not yet have the three-dimensional spatial resolution that is necessary in order to identify the intracranial anatomical structures that are involved in the generation of externally recorded activity and, thus, cannot yet inform us with precision about the anatomical substrates of neural events. In comparison, neuroimaging methods, such as positron emission tomography and functional magnetic resonance imaging, can provide higher spatial resolution information about which brain structures are involved in perceptual, motor, and cognitive processes. However, these imaging methods do not yield much information about the time course of brain activity. One promising approach is to combine electromagnetic recordings and functional neuroimaging in order to gain knowledge about the spatiotemporal organization of human cognition. Here we review how electrophysiology and functional neuroimaging can be combined in the study of attention in normal humans.     

Bootstrap assessment of the reliability of maxima in surface maps of brain activity of individual subjects derived with electrophysiological and optical methods

Surface maps of brain activity can be obtained with electrophysiological and optical recordings. However, there are no established methods for determining the reliability of maps of brain activity across subject groups or across tasks within the same subject. In this paper, we use bootstrapping to establish the reliability of the locations of maxima in maps of surface brain activity of individual subjects obtained with ERP and optical (EROS) recordings and report sample analyses for two data sets. Bootstrapping is a nonparametric method for estimating statistical accuracy from the data in a single sample. The distribution of the statistic of interest is estimated by constructing “bootstrap samples” from a pool of all available cases (with replacement). Many “bootstrap replications” are obtained by calculating the statistic of interest for each sample. In the case of brain activity, many (e.g., 10,000) amplitude distributions can be derived from the data of an individual subject. Frequency counts are then computed for each recording location to establish how many times that location corresponds to a maximum. The value obtained in this fashion represents an estimate of the reliability of the observation.     

Hierarchical organization of a reference system in newborn spontaneous movements

In this paper, we studied spontaneous newborn movements regarding the coordination of the four limbs, arms and legs, from a dynamic perspective. We used the method of recurrence plots to analyse the kinematic data from audiovisual recordings of neonates. We identified temporal and spatial synchronization of the four limbs that resulted in high recurrence patterns of biomechanical reference configurations. Furthermore, we identified transitions between linear and nonlinear epochs in the movement behavior of newborns on different time scales by means of recurrence quantification analysis. Results are discussed in the context of the concept of a structural hierarchy, in which different time scales correspond to hierarchical levels of organization.     

How to produce personality neuroscience research with high statistical power and low additional cost

Personality neuroscience involves examining relations between cognitive or behavioral variability and neural variables like brain structure and function. Such studies have uncovered a number of fascinating associations but require large samples, which are expensive to collect. Here, we propose a system that capitalizes on neuroimaging data commonly collected for separate purposes and combines it with new behavioral data to test novel hypotheses. Specifically, we suggest that groups of researchers compile a database of structural (i.e., anatomical) and resting-state functional scans produced for other task-based investigations and pair these data with contact information for the participants who contributed the data. This contact information can then be used to collect additional cognitive, behavioral, or individual-difference data that are then reassociated with the neuroimaging data for analysis. This would allow for novel hypotheses regarding brain–behavior relations to be tested on the basis of large sample sizes (with adequate statistical power) for low additional cost. This idea can be implemented at small scales at single institutions, among a group of collaborating researchers, or perhaps even within a single lab. It can also be implemented at a large scale across institutions, although doing so would entail a number of additional complications.     

Neural representations of location outside the hippocampus

Place cells of the rat hippocampus are a dominant model system for understanding the role of the hippocampus in learning and memory at the level of single-unit and neural ensemble responses. A complete understanding of the information processing and computations performed by the hippocampus requires detailed knowledge about the properties of the representations that are present in hippocampal afferents and efferents in order to decipher the transformations that occur to these representations in the hippocampal circuitry. Neural recordings in behaving rats have revealed a number of brain areas that contain place-related firing properties in the parahippocampal regions and in other brain regions that are thought to interact with the hippocampus in certain behavioral tasks. Although investigators have just begun to scratch the surface in terms of understanding these properties, differences in the precise nature of the spatial firing between the hippocampus and these other regions promise to reveal important clues regarding the exact role of the hippocampus in learning and memory and the nature of its interactions with other brain systems to support adaptive behavior.     

Temporal lobe signs: electroencephalographic validity and enhanced scores in special populations

Internal and external validity tests were completed for an inventory that has been used to infer signs of temporal lobe lability. Strong, positive correlations were reported for a normal (reference) population between the numbers of responses that referred to paranormal experiences (including feelings of a "presence") and separately to religious beliefs and the numbers of spikes per minute within electroencephalographic recordings from the temporal lobe. Numbers of spikes were also correlated with the subjects' scores on the hysteria, schizophrenia, and psychasthenia scales from the MMPI. These clusters of items were not correlated with electrical activity from the occipital lobe (the comparison region). Numbers of responses to control clusters of mundane experiences were not correlated with the temporal lobe measures. A group of student poets scored higher on different subclusters of temporal lobe signs and on the schizophrenia and mania scales of the MMPI than the reference group. For both groups, there were positive correlations between the amount of alpha activity in the temporal lobe only and answers to items such as "hearing inner voices" and "feeling as if things were not real." These results demonstrate that quantitative measures of electrical changes in the temporal lobe are correlated with (or with the report of) specific experiences that are prevalent during surgical or epileptic stimulation of this brain region.     

Development and validation of brief measures of positive and negative affect: the PANAS scales

In recent studies of the structure of affect, positive and negative affect have consistently emerged as two dominant and relatively independent dimensions. A number of mood scales have been created to measure these factors; however, many existing measures are inadequate, showing low reliability or poor convergent or discriminant validity. To fill the need for reliable and valid Positive Affect and Negative Affect scales that are also brief and easy to administer, we developed two 10-item mood scales that comprise the Positive and Negative Affect Schedule (PANAS). The scales are shown to be highly internally consistent, largely uncorrelated, and stable at appropriate levels over a 2-month time period. Normative data and factorial and external evidence of convergent and discriminant validity for the scales are also presented.     

Discovering oscillatory interaction networks with M/EEG: challenges and breakthroughs

The systems-level neuronal mechanisms that coordinate temporally, anatomically and functionally distributed neuronal activity into coherent cognitive operations in the human brain have remained poorly understood. Synchronization of neuronal oscillations may regulate network communication and could thus serve as such a mechanism. Evidence for this hypothesis, however, was until recently sparse, as methodological challenges limit the investigation of interareal interactions with non-invasive magneto- and electroencephalography (M/EEG) recordings. Nevertheless, recent advances in M/EEG source reconstruction and clustering methods support complete phase-interaction mappings that are essential for uncovering the large-scale neuronal assemblies and their functional roles. These data show that synchronization is a robust and behaviorally significant phenomenon in task-relevant cortical networks and could hence bind distributed neuronal processing to coherent cognitive states.     

The effects of biasing information on behavioral observations and rating scales

The effects of biasing information on behavioral observations and rating scales were studied. Fortyone undergraduate students trained in making reliable behavioral observations were given differential expectations concerning the activity level of a target child. They then viewed videotape recordings of that child and tallied frequency counts of six behavioral categories simultaneously. In addition, subjects completed postexperimental rating scales composed of specific, identifiable behaviors in regard to the target child. Results indicated that, for the most part, neither the behavioral observations nor the rating scales were significantly affected by the biasing information. It is suggested that rating scales constructed of items as discrete and readily identifiable as those of behavioral observation measures may prove resistant to biasing effects.This study is based in part on a thesis submitted by the second author to Case Western Reserve University in partial fulfillment of the requirements for the master of arts degree in psychology. The authors express their appreciation to the Claremont Unified School District, Claremont, California, for their assistance in the production of the videotape and to the Instructional Support Center at Case Western Reserve University for their co-operation in providing research space. Special thanks are given to Thomas Hyde for his advice and assistance throughout the study.     

Multisensory self‐motion encoding in parietal cortex

Navigation through the environment requires the brain to process a number of incoming sensory signals, such as visual optical flow on the retina and motion information originating from the vestibular organs. In addition, tactile as well as auditory signals can help to disambiguate the continuous stream of incoming information and determining the signals resulting from one's own set of motion. In this review I will focus on the cortical processing of motion information in one subregion of the posterior parietal cortex, i.e., the ventral intraparietal area (VIP). I will review (1) electrophysiological data from single cell recordings in the awake macaque showing how self‐motion signals across different sensory modalities are represented within this area and (2) data from fMRI recordings in normal human subjects providing evidence for the existence of a functionally equivalent area of macaque area VIP in the human cortex.     

A mechanism for cognitive dynamics: neuronal communication through neuronal coherence

At any one moment, many neuronal groups in our brain are active. Microelectrode recordings have characterized the activation of single neurons and fMRI has unveiled brain-wide activation patterns. Now it is time to understand how the many active neuronal groups interact with each other and how their communication is flexibly modulated to bring about our cognitive dynamics. I hypothesize that neuronal communication is mechanistically subserved by neuronal coherence. Activated neuronal groups oscillate and thereby undergo rhythmic excitability fluctuations that produce temporal windows for communication. Only coherently oscillating neuronal groups can interact effectively, because their communication windows for input and for output are open at the same times. Thus, a flexible pattern of coherence defines a flexible communication structure, which subserves our cognitive flexibility.     

Comparison of magneto-and electroencephalographic techniques in event-related response research—a brief survey

Event-related brain potentials are widely used in psychophysiological and neurophysiological research. Recently it has become possible to record weak magnetic fields associated with the electric events of the human brain. In this short survey the magnetoencephalo-graphic (MEG) techniques are compared with the conventional electric measures. MEG and EEG are sensitive to current sources of different orientation. Extracerebral tissues smear and damp the electric potentials but they do not have any significant effect on the magnetic fields. EEG measures potential differences whereas the actual current paths determine the magnetic fields measured outside the skull. In general MEG provides better spatial resolution than the electric recordings, as far as the cortical sources are concerned. It is concluded that EEG and MEG are complementary noninvasive techniques in brain research. As an example slow EEG and MEG shifts preceding voluntary foot movements are compared.     

Deictic codes for the embodiment of cognition

To describe phenomena that occur at different time scales, computational models of the brain must incorporate different levels of abstraction. At time scales of approximately 1/3 of a second, orienting movements of the body play a crucial role in cognition and form a useful computational level--more abstract than that used to capture natural phenomena but less abstract than what is traditionally used to study high-level cognitive processes such as reasoning. At this "embodiment level," the constraints of the physical system determine the nature of cognitive operations. The key synergy is that at time scales of about 1/3 of a second, the natural sequentiality of body movements can be matched to the natural computational economies of sequential decision systems through a system of implicit reference called deictic in which pointing movements are used to bind objects in the world to cognitive programs. This target article focuses on how deictic binding make it possible to perform natural tasks. Deictic computation provides a mechanism for representing the essential features that link external sensory data with internal cognitive programs and motor actions. One of the central features of cognition, working memory, can be related to moment-by-moment dispositions of body features such as eye movements and hand movements.     

Reading the hippocampal code by theta phase-locking

Both the prefrontal cortex and the hippocampus are crucial for memory encoding and recall. However, it remains unclear how these brain regions communicate to exchange information. Recent findings using simultaneous recordings from the hippocampus and prefrontal cortex of the behaving rat have demonstrated that prefrontal cells' firing is phase-locked to the hippocampal theta rhythm. This suggests that phase synchronization clocked by the theta rhythm could be crucial for the communication between hippocampal and prefrontal regions.     

A hierarchy of cortical responses to sequence violations in three-month-old infants

The adult human brain quickly adapts to regular temporal sequences, and emits a sequence of novelty responses when these regularities are violated. These novelty responses have been interpreted as error signals that reflect the difference between the incoming signal and predictions generated at multiple cortical levels. Do infants already possess such a hierarchy of violation-detection mechanisms? Using high-density recordings of event-related potentials during an auditory local–global violation paradigm, we show that three-month-old infants process novelty in temporal sequences at two distinct levels. Violations of local expectancies, such as perceiving a deviant vowel “a” after repeated presentation of another vowel i-i-i, elicited an early auditory mismatch response. Conversely, violations of global expectancies, such as hearing the rare sequence a-a-a-a instead of the frequent sequence a-a-a-i, modulated this early mismatch response and led to a late frontal negative slow wave, whose cortical sources included the left inferior frontal region. These results suggest that the infant brain already possesses two dissociable systems for temporal sequence learning.     

A generative joint model for spike trains and saccades during perceptual decision-making

Theory development in both psychology and neuroscience can benefit by consideration of both behavioral and neural data sets. However, the development of appropriate methods for linking these data sets is a difficult statistical and conceptual problem. Over the past decades, different linking approaches have been employed in the study of perceptual decision-making, beginning with rudimentary linking of the data sets at a qualitative, structural level, culminating in sophisticated statistical approaches with quantitative links. We outline a new approach, in which a single model is developed that jointly addresses neural and behavioral data. This approach allows for specification and testing of quantitative links between neural and behavioral aspects of the model. Estimating the model in a Bayesian framework allows both data sets to equally inform the estimation of all model parameters. The use of a hierarchical model architecture allows for a model, which accounts for and measures the variability between neurons. We demonstrate the approach by re-analysis of a classic data set containing behavioral recordings of decision-making with accompanying single-cell neural recordings. The joint model is able to capture most aspects of both data sets, and also supports the analysis of interesting questions about prediction, including predicting the times at which responses are made, and the corresponding neural firing rates.     

Individual differences in FFA activity suggest independent processing at different spatial scales

The brain processes images at different spatial scales, but it is unclear how far into the visual stream different scales remain segregated. Using functional magnetic resonance imaging, we found evidence that BOLD activity in the fusiform face area (FFA) reflects computations based on separate spatial frequency inputs. When subjects perform different tasks (attend location vs. identity; attend whole vs. parts) or the same task with different stimuli (upright or inverted) with high- and low-pass images of cars and faces, individual differences in the FFA in one condition are correlated with those in the other condition. However, FFA activity in response to low-pass stimuli is independent of its response to highpass stimuli. These results suggest that spatial scales are not integrated before the FFA and that processing in this area could support the flexible use of different sources of information present in broad-pass images.     

When, where, what: the electromagnetic contribution to the WWW of brain activity during recognition

Recent findings from event-related potential (ERP) as well as hemodynamic studies have provided physiological evidence that recognition memory involves task-related brain processes, notably episodic retrieval mode, and item-related brain processes, notably retrieval success or ecphory. The excellent time resolution of electromagnetic techniques allows to study the time course of these processes on a time range from milliseconds to several seconds. In a series of studies, the time scales within which task- and item-related processes are likely to operate were investigated. The results raise the possibility that both types of processes are further fractionable into short and longlasting components. The cognitive underpinnings of these components have yet to be determined.     

The functional role of cross-frequency coupling

Recent studies suggest that cross-frequency coupling (CFC) might play a functional role in neuronal computation, communication and learning. In particular, the strength of phase-amplitude CFC differs across brain areas in a task-relevant manner, changes quickly in response to sensory, motor and cognitive events, and correlates with performance in learning tasks. Importantly, whereas high-frequency brain activity reflects local domains of cortical processing, low-frequency brain rhythms are dynamically entrained across distributed brain regions by both external sensory input and internal cognitive events. CFC might thus serve as a mechanism to transfer information from large-scale brain networks operating at behavioral timescales to the fast, local cortical processing required for effective computation and synaptic modification, thus integrating functional systems across multiple spatiotemporal scales.