From active affordance to active inference: vertical integration of cognition in the cerebral cortex through dual subcortical control systems.

In previous papers, we proposed that the dorsal attention system's top-down control is regulated by the dorsal division of the limbic system, providing a feedforward or impulsive form of control generating expectancies during active inference. In contrast, we proposed that the ventral attention system is regulated by the ventral limbic division, regulating feedback constraints and error-correction for active inference within the neocortical hierarchy. Here, we propose that these forms of cognitive control reflect vertical integration of subcortical arousal control systems that evolved for specific forms of behavior control. The feedforward impetus to action is regulated by phasic arousal, mediated by lemnothalamic projections from the reticular activating system of the lower brainstem, and then elaborated by the hippocampus and dorsal limbic division. In contrast, feedback constraint-based on environmental requirements-is regulated by the tonic activation furnished by collothalamic projections from the midbrain arousal control centers, and then sustained and elaborated by the amygdala, basal ganglia, and ventral limbic division. In an evolutionary-developmental analysis, understanding these differing forms of active affordance-for arousal and motor control within the subcortical vertebrate neuraxis-may help explain the evolution of active inference regulating the cognition of expectancy and error-correction within the mammalian 6-layered neocortex.

Continuity and change in neural plasticity through embryonic morphogenesis, fetal activity-dependent synaptogenesis, and infant memory consolidation.

There is an apparent continuity in human neural development that can be traced to venerable themes of vertebrate morphogenesis that have shaped the evolution of the reptilian telencephalon (including both primitive three-layered cortex and basal ganglia) and then the subsequent evolution of the mammalian six-layered neocortex. In this theoretical analysis, we propose that an evolutionary-developmental analysis of these general morphogenetic themes can help to explain the embryonic development of the dual divisions of the limbic system that control the dorsal and ventral networks of the human neocortex. These include the archicortical (dorsal limbic) Papez circuits regulated by the hippocampus that organize spatial, contextual memory, as well as the paleocortical (ventral limbic) circuits that organize object memory. We review evidence that these dorsal and ventral limbic divisions are controlled by the differential actions of brainstem lemnothalamic and midbrain collothalamic arousal control systems, respectively, thereby traversing the vertebrate subcortical neuraxis. These dual control systems are first seen shaping the phyletic morphogenesis of the archicortical and paleocortical foundations of the forebrain in embryogenesis. They then provide dual modes of activity-dependent synaptic organization in the active (lemnothalamic) and quiet (collothalamic) stages of fetal sleep. Finally, these regulatory systems mature to form the major systems of memory consolidation of postnatal development, including the rapid eye movement (lemnothalamic) consolidation of implicit memory and social attachment in the first year, and then-in a subsequent stage-the non-REM (collothalamic) consolidation of explicit memory that is integral to the autonomy and individuation of the second year of life.

Adaptive control of functional connectivity: dorsal and ventral limbic divisions regulate the dorsal and ventral neocortical networks.

The connectional anatomy of the primate cortex is now well-defined by the Structural Model, in which adjacent cortical areas are interconnected in an organized network hierarchy of communication and control. The computational theory of "active inference" can be aligned with this architecture, proposing that predictions descend from higher association areas to be updated by ascending prediction errors from lower (i.e. primary) sensory and motor areas. Given the connectivity, the limbic networks at the apex of the cerebral hierarchy must then be responsible for the most general expectancies, which are propagated through the hierarchy to organize the multiple component network levels of experience and behavior. Anatomical evidence suggests that there are dual limbic divisions, reflecting archicortical (dorsal) and paleocortical (ventral) derivations, resulting in fundamentally different neural mechanisms for managing expectancies across the corticolimbic hierarchy. In the functional connectivity literature, the dorsal attention network is seen to provide top-down or endogenous control of attention, whereas the ventral attention network provides stimulus bound or exogenous attentional control. We review evidence indicating that the dorsal, archicortical division of the limbic system provides a feedforward, impulsive, endogenous mode of motive control, whereas the ventral, paleocortical limbic division provides feedback constraint linked to exogenous events.

Neurophysiological mechanisms of implicit and explicit memory in the process of consciousness.

Neurophysiological mechanisms are increasingly understood to constitute the foundations of human conscious experience. These include the capacity for ongoing memory, achieved through a hierarchy of reentrant cross-laminar connections across limbic, heteromodal, unimodal, and primary cortices. The neurophysiological mechanisms of consciousness also include the capacity for volitional direction of attention to the ongoing cognitive process, through a reentrant fronto-thalamo-cortical network regulation of the inhibitory thalamic reticular nucleus. More elusive is the way that discrete objects of subjective experience, such as the color of deep blue or the sound of middle C, could be generated by neural mechanisms. Explaining such ineffable qualities of subjective experience is what Chalmers has called "the hard problem of consciousness," which has divided modern neuroscientists and philosophers alike. We propose that insight into the appearance of the hard problem can be gained through integrating classical phenomenological studies of experience with recent progress in the differential neurophysiology of consolidating explicit versus implicit memory. Although the achievement of consciousness, once it is reflected upon, becomes explicit, the underlying process of generating consciousness, through neurophysiological mechanisms, is largely implicit. Studying the neurophysiological mechanisms of adaptive implicit memory, including brain stem, limbic, and thalamic regulation of neocortical representations, may lead to a more extended phenomenological understanding of both the neurophysiological process and the subjective experience of consciousness.NEW & NOTEWORTHY The process of consciousness, generating the qualia that may appear to be irreducible qualities of experience, can be understood to arise from neurophysiological mechanisms of memory. Implicit memory, organized by the lemnothalamic brain stem projections and dorsal limbic consolidation in REM sleep, supports the unconscious field and the quasi-conscious fringe of current awareness. Explicit memory, organized by the collothalamic midbrain projections and ventral limbic consolidation of NREM sleep, supports the focal objects of consciousness.

Focal limbic sources create the large slow oscillations of the EEG in human deep sleep.

BACKGROUND: Initial observations with the human electroencephalogram (EEG) have interpreted slow oscillations (SOs) of the EEG during deep sleep (N3) as reflecting widespread surface-negative traveling waves that originate in frontal regions and propagate across the neocortex. However, mapping SOs with a high-density array shows the simultaneous appearance of posterior positive voltage fields in the EEG at the time of the frontal-negative fields, with the typical inversion point (apparent source) around the temporal lobe. METHODS: Overnight 256-channel EEG recordings were gathered from 10 healthy young adults. Individual head conductivity models were created using each participant's own structural MRI. Source localization of SOs during N3 was then performed. RESULTS: Electrical source localization models confirmed that these large waves were created by focal discharges within the ventral limbic cortex, including medial temporal and caudal orbitofrontal cortex. CONCLUSIONS: Although the functional neurophysiology of deep sleep involves interactions between limbic and neocortical networks, the large EEG deflections of deep sleep are not created by distributed traveling waves in lateral neocortex but instead by relatively focal limbic discharges.

Motive control of unconscious inference: The limbic base of adaptive Bayes.

Current computational models of neocortical processing, described as predictive coding theory, are providing new ways of understanding Helmholtz's classical insight that perception cannot proceed in a data-driven fashion, but instead requires unconscious inference based on prior experience. Predictive coding is a Bayesian process, in which the operations at each lower level of the cortical hierarchy are predicted by prior projections of expectancies from a higher level, and are then updated by error-correction with lower level evidence. To generalize the predictive coding model to the human neocortex as a whole requires aligning the Bayesian negotiation of prior expectancies with sensory and motor evidence not only within the connectional architecture of the neocortex (primary sensory/motor, unimodal association areas, and heteromodal association areas) but also with the limbic cortex that forms the base for the adaptive control of the heteromodal areas and thereby the cerebral hemisphere as a whole. By reviewing the current evidence on the anatomy of the human corticolimbic connectivity (now formalized as the Structural Model) we address the problem of how limbic cortex resonates to the homeostatic, personal significance of events to provide Bayesian priors to organize the operations of predictive coding across the multiple levels of the neocortex. By reviewing both classical evidence and current models of control exerted between limbic and neocortical networks, we suggest a neuropsychological theory of human cognition, the adaptive Bayes process model, in which prior expectancies are not simply rationalized propositions, but rather affectively-charged expectancies that bias the interpretation of sensory data and action affordances to support allostasis, the motive control of expectancies for future events.

Transcranial Electrical Stimulation targeting limbic cortex increases the duration of human deep sleep.

BACKGROUND: Researchers have proposed that impaired sleep may be a causal link in the progression from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD). Several recent findings suggest that enhancing deep sleep (N3) may improve neurological health in persons with MCI, and buffer the risk for AD. Specifically, Transcranial Electrical Stimulation (TES) of frontal brain areas, the inferred source of the Slow Oscillations (SOs) of N3 sleep, can extend N3 sleep duration and improve declarative memory for recently learned information. Recent work in our laboratory using dense array Electroencephalography (dEEG) localized the sources of SOs to anterior limbic sites - suggesting that targeting these sites with TES may be more effective for enhancing N3. METHODS: For the present study, we recruited 13 healthy adults (M = 42 years) to participate in three all-night sleep EEG recordings where they received low level (0.5 mA) TES designed to target anterior limbic areas and a sham stimulation (placebo). We used a convolutional neural network, trained and tested on professionally scored EEG sleep staging, to predict sleep stages for each recording. RESULTS: When compared to the sham session, limbic-targeted TES significantly increased the duration of N3 sleep. TES also significantly increased spectral power in the 0.5-1 Hz frequency band (relative to pre-TES epochs) in left temporoparietal and left occipital scalp regions compared to sham. CONCLUSION: These results suggest that even low-level TES, when specifically targeting anterior limbic sites, can increase deep (N3) sleep and thereby contribute to healthy sleep quality.

Safety of slow-pulsed transcranial electrical stimulation in acute spike suppression.

We examined the effects of slow-pulsed transcranial electrical stimulation (TES) in suppressing epileptiform discharges in seven adults with refractory epilepsy. An MRI-based realistic head model was constructed for each subject and co-registered with 256-channel dense EEG (dEEG). Interictal spikes were localized, and TES targeted the cortical source of each subject's principal spike population. Targeted spikes were suppressed in five subject's (29/35 treatment days overall), and nontargeted spikes were suppressed in four subjects. Epileptiform activity did not worsen. This study suggests that this protocol, designed to induce long-term depression (LTD), is safe and effective in acute suppression of interictal epileptiform discharges.

EEG source imaging of epileptic activity at seizure onset.

Surgical resection of the seizure onset zone (SOZ) requires that this region of the cortex is accurately localized. The onset of a seizure may be marked by transient discharges, but it also may be accompanied by oscillatory, sinusoidal electrographic activity, such as the EEG theta rhythm. However, because of the superposition of the seizure signal with other electrical signals, including noise artifacts and non-seizure brain activity, noninvasive Electrical Source Imaging (ESI) of the ictal EEG activity at seizure onset remains a challenging task for surgical planning. In the present study, we localize the SOZ from oscillatory features of the EEG at the ictal onset using 256-channel high density electroencephalography (HD-EEG), exact sensor positions, and individual electrical head models constructed from the patient's T1 magnetic resonance image (MRI). Epileptic activities at the seizure onset were characterized with joint time-frequency analysis and source estimated by standardized low resolution electromagnetic tomography (sLORETA) inverse method. The consistency of this localization was examined across multiple seizures for individual patients. For validation, results were compared to three clinical criteria: (1) epileptogenic lesions, (2) seizure onset observed in intracranial EEG, and (3) successful surgical outcomes. In this set of 84 seizures, the onsets of 56 seizures could be localized. For the lateralization measure, the results from HD-EEG with interictal spikes (8/10) and with ictal onset (10/10) were more accurate than international 10-20 EEG for interictal spikes (5/10) and ictal onset (5/10). ESI from HD-EEG with ictal onset (9/10) had greater concordance to the clinical criteria than HD-EEG with interictal spikes (6/10). Noninvasive ESI of oscillatory features at ictal onset using 256-channel HD-EEG and high-resolution individual head models can make a useful contribution to the clinical localization of the SOZ in presurgical planning.

Dynamic Responses in Brain Networks to Social Feedback: A Dual EEG Acquisition Study in Adolescent Couples.

Adolescence is a sensitive period for the development of romantic relationships. During this period the maturation of frontolimbic networks is particularly important for the capacity to regulate emotional experiences. In previous research, both functional magnetic resonance imaging (fMRI) and dense array electroencephalography (dEEG) measures have suggested that responses in limbic regions are enhanced in adolescents experiencing social rejection. In the present research, we examined social acceptance and rejection from romantic partners as they engaged in a Chatroom Interact Task. Dual 128-channel dEEG systems were used to record neural responses to acceptance and rejection from both adolescent romantic partners and unfamiliar peers (N = 75). We employed a two-step temporal principal component analysis (PCA) and spatial independent component analysis (ICA) approach to statistically identify the neural components related to social feedback. Results revealed that the early (288 ms) discrimination between acceptance and rejection reflected by the P3a component was significant for the romantic partner but not the unfamiliar peer. In contrast, the later (364 ms) P3b component discriminated between acceptance and rejection for both partners and peers. The two-step approach (PCA then ICA) was better able than either PCA or ICA alone in separating these components of the brain's electrical activity that reflected both temporal and spatial phases of the brain's processing of social feedback.

Slow-Frequency Pulsed Transcranial Electrical Stimulation for Modulation of Cortical Plasticity Based on Reciprocity Targeting with Precision Electrical Head Modeling.

In pain management as well as other clinical applications of neuromodulation, it is important to consider the timing parameters influencing activity-dependent plasticity, including pulsed versus sustained currents, as well as the spatial action of electrical currents as they polarize the complex convolutions of the cortical mantle. These factors are of course related; studying temporal factors is not possible when the spatial resolution of current delivery to the cortex is so uncertain to make it unclear whether excitability is increased or decreased with anodal vs. cathodal current flow. In the present study we attempted to improve the targeting of specific cortical locations by applying current through flexible source-sink configurations of 256 electrodes in a geodesic array. We constructed a precision electric head model for 12 healthy individuals. Extraction of the individual's cortical surface allowed computation of the component of the induced current that is normal to the target cortical surface. In an effort to replicate the long-term depression (LTD) induced with pulsed protocols in invasive animal research and transcranial magnetic stimulation studies, we applied 100 ms pulses at 1.9 s intervals either in cortical-surface-anodal or cortical-surface-cathodal directions, with a placebo (sham) control. The results showed significant LTD of the motor evoked potential as a result of the cortical-surface-cathodal pulses in contrast to the placebo control, with a smaller but similar LTD effect for anodal pulses. The cathodal LTD after-effect was sustained over 90 min following current injection. These results support the feasibility of pulsed protocols with low total charge in non-invasive neuromodulation when the precision of targeting is improved with a dense electrode array and accurate head modeling.

BrainK for Structural Image Processing: Creating Electrical Models of the Human Head.

BrainK is a set of automated procedures for characterizing the tissues of the human head from MRI, CT, and photogrammetry images. The tissue segmentation and cortical surface extraction support the primary goal of modeling the propagation of electrical currents through head tissues with a finite difference model (FDM) or finite element model (FEM) created from the BrainK geometries. The electrical head model is necessary for accurate source localization of dense array electroencephalographic (dEEG) measures from head surface electrodes. It is also necessary for accurate targeting of cerebral structures with transcranial current injection from those surface electrodes. BrainK must achieve five major tasks: image segmentation, registration of the MRI, CT, and sensor photogrammetry images, cortical surface reconstruction, dipole tessellation of the cortical surface, and Talairach transformation. We describe the approach to each task, and we compare the accuracies for the key tasks of tissue segmentation and cortical surface extraction in relation to existing research tools (FreeSurfer, FSL, SPM, and BrainVisa). BrainK achieves good accuracy with minimal or no user intervention, it deals well with poor quality MR images and tissue abnormalities, and it provides improved computational efficiency over existing research packages.

An improved artifacts removal method for high dimensional EEG.

BACKGROUND: Multiple noncephalic electrical sources superpose with brain signals in the recorded EEG. Blind source separation (BSS) methods such as independent component analysis (ICA) have been shown to separate noncephalic artifacts as unique components. However, robust and objective identification of artifact components remains a challenge in practice. In addition, with high dimensional data, ICA requires a large number of observations for stable solutions. Moreover, using signals from long recordings to provide the large observation set might violate the stationarity assumption of ICA due to signal changes over time. NEW METHOD: Instead of decomposing all channels simultaneously, subsets of channels are randomly selected and decomposed with ICA. With reduced dimensionality of the subsets, much less amount of data is required to derive stable components. To characterize each independent component, an artifact relevance index (ARI) is calculated by template matching each component with a model of the artifact. Automatic artifact identification is then implemented based on the statistical distribution of ARI of the numerous components generated. RESULTS: The proposed permutation resampling for identification matching (PRIM) method effectively removed eye blink artifacts from both simulated and real EEG. COMPARISON WITH EXISTING METHOD: The average topomap correlation coefficient between the cleaned EEG and the ground truth is 0.89±0.01 for PRIM, compared with 0.64±0.05 for conventional ICA based method. The average relative root-mean-square error is 0.40±0.01 for PRIM, compared with 0.66±0.10 for conventional method. CONCLUSIONS: The proposed method overcame limitations of conventional ICA based method and succeeded in removing eye blink artifacts automatically.

Principal components of electrocortical activity during self-evaluation indicate depressive symptom severity.

Negative self-evaluation is an important psychological characteristic of depression. In order to study the underlying neural mechanisms, we examined event-related potentials (ERPs) during a self-evaluation task in a community sample (N = 150) of adults reporting a range of depressive symptoms. Principal components analysis (PCA) was used to separate processes that overlap in the average ERP, and neural source analysis was applied to localize the ERP components, with a particular focus on the frontal networks that are thought to be critical to affective self-regulation in depression. Consistent with previous research, individuals reporting greater depression showed enhanced negativity over medial frontal regions as well as attenuation of the late positive potential over parietal regions. Examining loadings of frontal sources on the ERP components showed that activity in the right inferior frontal region may be particularly important for depressed individuals: activity in this region declined as symptoms became more severe. Characterizing brain mechanisms of self-evaluation on the timescale of cognitive events may provide insight into the neural mechanisms of self-regulation that are important in cognitive therapy, and that could be made more amenable to change through increasing neuroplasticity with targeted non-invasive neuromodulation.

Changes in P3b Latency and Amplitude Reflect Expertise Acquisition in a Football Visuomotor Learning Task.

Learning is not a unitary phenomenon. Rather, learning progresses through stages, with the stages reflecting different challenges that require the support of specific cognitive processes that reflect the functions of different brain networks. A theory of general learning proposes that learning can be divided into early and late stages controlled by corticolimbic networks located in frontal and posterior brain regions, respectively. Recent human studies using dense-array EEG (dEEG) support these results by showing progressive increases in P3b amplitude (an Event Related Potential with estimated sources in posterior cingulate cortex and hippocampus) as participants acquire a new visuomotor skill. In the present study, the P3b was used to track the learning and performance of participants as they identify defensive football formations and make an appropriate response. Participants acquired the task over three days, and P3b latency and amplitude significantly changed when participants learned the task. As participants demonstrated further proficiency with extensive training, amplitude and latency changes in the P3b continued to closely mirror performance improvements. Source localization results across all days suggest that an important source generator of the P3b is located in the posterior cingulate cortex. Results from the study support prior findings and further suggest that the careful analysis of covert learning mechanisms and their underlying electrical signatures are a robust index of task competency.

Critical periods for the neurodevelopmental processes of externalizing and internalizing.

Research on neurobiological development is providing insight into the nature and mechanisms of human neural plasticity. These mechanisms appear to support two different forms of developmental learning. One form of learning could be described as externalizing, in which neural representations are highly responsive to environmental influences, as the child typically operates under a mode of hedonic approach. A second form of learning supports internalizing, in which motive control separates attention and self-regulation from the immediate influences of the context, particularly when the child faces conditions of avoidance and threat. The dorsal cortical networks of externalizing are organized around dorsal limbic (cingulate, septal, lateral hypothalamic, hippocampal, and ventral striatal) circuits. In contrast, the ventral cortical networks of internalizing are organized around ventral limbic (anterior temporal and orbital cortex, extended amygdala, dorsal striatal, and mediodorsal thalamic) circuits. These dual divisions of the limbic system in turn self-regulate their arousal levels through different brain stem and forebrain neuromodulator projection systems, with dorsal corticolimbic networks regulated strongly by locus coeruleus norepinephrine and brain stem raphe nucleus serotonin projection systems, and ventral corticolimbic networks regulated by ventral tegmental dopamine and forebrain acetylcholine projections. Because the arousal control systems appear to regulate specific properties of neural plasticity in development, an analysis of these systems explains differences between externalizing and internalizing at multiple levels of neural and psychological self-regulation. In neuroscience, the concept of critical periods has been applied to times when experience is essential for the maturation of sensory systems. In a more general neuropsychological analysis, certain periods of the child's development require successful self-regulation through the differential capacities for externalizing and internalizing.

Localizing movement-related primary sensorimotor cortices with multi-band EEG frequency changes and functional MRI.

Electroencephalographic (EEG) oscillations in multiple frequency bands can be observed during functional activity of the cerebral cortex. An important question is whether activity of focal areas of cortex, such as during finger movements, is tracked by focal oscillatory EEG changes. Although a number of studies have compared EEG changes to functional MRI hemodynamic responses, we can find no previous research that relates the fMRI hemodynamic activity to localization of the multiple EEG frequency changes observed in motor tasks. In the present study, five participants performed similar thumb and finger movement tasks in parallel EEG and functional MRI studies. We examined changes in five frequency bands (from 5-120 Hz) and localized them using 256 dense-array EEG (dEEG) recordings and high-resolution individual head models. These localizations were compared with fMRI localizations in the same participants. Results showed that beta-band (14-30 Hz) desynchronizations (power decreases) were the most robust effects, appearing in all individuals, consistently localized to the hand region of the primary motor cortex, and consistently aligned with fMRI localizations.

Time-course of cortical networks involved in working memory.

Working memory (WM) is one of the most studied cognitive constructs. Although many neuroimaging studies have identified brain networks involved in WM, the time course of these networks remains unclear. In this paper we use dense-array electroencephalography (dEEG) to capture neural signals during performance of a standard WM task, the n-back task, and a blend of principal components analysis and independent components analysis (PCA/ICA) to statistically identify networks of WM and their time courses. Results reveal a visual cortex centric network, that also includes the posterior cingulate cortex, that is active prior to stimulus onset and that appears to reflect anticipatory, attention-related processes. After stimulus onset, the ventromedial prefrontal cortex, lateral prefrontal prefrontal cortex, and temporal poles become associated with the prestimulus network. This second network appears to reflect executive control processes. Following activation of the second network, the cortices of the temporo-parietal junction with the temporal lobe structures seen in the first and second networks re-engage. This third network appears to reflect activity of the ventral attention network involved in control of attentional reorientation. The results point to important temporal features of network dynamics that integrate multiple subsystems of the ventral attention network with the default mode network in the performance of working memory tasks.

Corrigendum: Dense Array EEG Source Estimation in Neocortical Epilepsy.

[This corrects the article on p. 42 in vol. 4, PMID: 23717298.].