Central Nervous System Changes in Pediatric Heart Failure: A Volumetric Study

Autonomic dysfunction, mood disturbances, and memory deficits appear in pediatric and adult heart failure (HF). Brain areas controlling these functions show injury in adult HF patients, many of whom have comorbid cerebrovascular disease. We examined whether similar brain pathology develops in pediatric subjects without such comorbidities. In this study, high-resolution T1 brain magnetic resonance images were collected from seven severe HF subjects age (age 8–18 years [mean 13]; left ventricular shortening 9 to 19% [median 14%]) and seven age-matched healthy controls (age 8–18 years [mean 13]). After segmentation into gray matter (GM), white matter, and cerebrospinal fluid (CSF), regional volume loss between groups was determined by voxel-based morphometry. GM volume loss appeared on all HF scans, but ischemic changes and infarcts were absent. HF subjects showed greater CSF volume than controls (mean ± SD 0.30 ± 0.04 vs. 0.25 ± 0.04 l, P = 0.03), but total intracranial volume was identical (1.39 ± 0.11 vs. 1.39 ± 0.09 l, P = NS). Regional GM volume reduction appeared in the right and left posterior hippocampus, bilateral mid-insulae, and the superior medial frontal gyrus and mid-cingulate cortex of HF subjects (threshold P < 0.001). No volume-loss sites appeared in control brains. We conclude that pediatric HF patients show brain GM loss in areas similar to those of adult HF subjects. Substantial changes emerged in sites that regulate autonomic function as well as mood, personality and short-term memory. In the absence of thromboembolic disease and many comorbid conditions found in adult HF patients, pediatric HF patients show significant, focal GM volume loss, which may coincide with the multiple neurologic and psychological changes observed in patients with HF

Differential Encoding of Factors Influencing Predicted Reward Value in Monkey Rostral Anterior Cingulate Cortex

Background: The value of a predicted reward can be estimated based on the conjunction of both the intrinsic reward value and the length of time to obtain it. The question we addressed is how the two aspects, reward size and proximity to reward, influence the responses of neurons in rostral anterior cingulate cortex (rACC), a brain region thought to play an important role in reward processing. Methods and Findings: We recorded from single neurons while two monkeys performed a multi-trial reward schedule task. The monkeys performed 1–4 sequential color discrimination trials to obtain a reward of 1–3 liquid drops. There were two task conditions, a valid cue condition, where the number of trials and reward amount were associated with visual cues, and a random cue condition, where the cue was picked from the cue set at random. In the valid cue condition, the neuronal firing is strongly modulated by the predicted reward proximity during the trials. Information about the predicted reward amount is almost absent at those times. In substantial subpopulations, the neuronal responses decreased or increased gradually through schedule progress to the predicted outcome. These two gradually modulating signals could be used to calculate the effect of time on the perception of reward value. In the random cue condition, little information about the reward proximity or reward amount is encoded during the course of the trial before reward delivery, but when the reward is actually delivered the responses reflect both the reward proximity and reward amount

Development of abstract thinking during childhood and adolescence: the role of rostrolateral prefrontal cortex

Rostral prefrontal cortex (RPFC) has increased in size and changed in terms of its cellular organisation during primate evolution. In parallel emerged the ability to detach oneself from the immediate environment to process abstract thoughts and solve problems and to understand other individuals’ thoughts and intentions. Rostrolateral prefrontal cortex (RLPFC) is thought to play an important role in supporting the integration of abstract, often self-generated, thoughts. Thoughts can be temporally abstract and relate to long term goals, or past or future events, or relationally abstract and focus on the relationships between representations rather than simple stimulus features. Behavioural studies have provided evidence of a prolonged development of the cognitive functions associated with RLPFC, in particular logical and relational reasoning, but also episodic memory retrieval and prospective memory. Functional and structural neuroimaging studies provide further support for a prolonged development of RLPFC during adolescence, with some evidence of increased specialisation of RLPFC activation for relational integration and aspects of episodic memory retrieval. Topics for future research will be discussed, such as the role of medial RPFC in processing abstract thoughts in the social domain, the possibility of training abstract thinking in the domain of reasoning, and links to education

Deep temporal models and active inference

How do we navigate a deeply structured world? Why are you reading this sentence first – and did you actually look at the fifth word? This review offers some answers by appealing to active inference based on deep temporal models. It builds on previous formulations of active inference to simulate behavioural and electrophysiological responses under hierarchical generative models of state transitions. Inverting these models corresponds to sequential inference, such that the state at any hierarchical level entails a sequence of transitions in the level below. The deep temporal aspect of these models means that evidence is accumulated over nested time scales, enabling inferences about narratives (i.e., temporal scenes). We illustrate this behaviour with Bayesian belief updating – and neuronal process theories – to simulate the epistemic foraging seen in reading. These simulations reproduce perisaccadic delay period activity and local field potentials seen empirically. Finally, we exploit the deep structure of these models to simulate responses to local (e.g., font type) and global (e.g., semantic) violations; reproducing mismatch negativity and P300 responses respectively

Neuronal correlates of decisions to speak and act: Spontaneous emergence and dynamic topographies in a computational model of frontal and temporal areas

The neural mechanisms underlying the spontaneous, stimulus-independent emergence of intentions and decisions to act are poorly understood. Using a neurobiologically realistic model of frontal and temporal areas of the brain, we simulated the learning of perception–action circuits for speech and hand-related actions and subsequently observed their spontaneous behaviour. Noise-driven accumulation of reverberant activity in these circuits leads to their spontaneous ignition and partial-to-full activation, which we interpret, respectively, as model correlates of action intention emergence and action decision-and-execution. Importantly, activity emerged first in higher-association prefrontal and temporal cortices, subsequently spreading to secondary and finally primary sensorimotor model-areas, hence reproducing the dynamics of cortical correlates of voluntary action revealed by readiness-potential and verb-generation experiments. This model for the first time explains the cortical origins and topography of endogenous action decisions, and the natural emergence of functional specialisation in the cortex, as mechanistic consequences of neurobiological principles, anatomical structure and sensorimotor experience

From sensorimotor learning to memory cells in prefrontal and temporal association cortex: A neurocomputational study of disembodiment

Memory cells, the ultimate neurobiological substrates of working memory, remain active for several seconds and are most commonly found in prefrontal cortex and higher multisensory areas. However, if correlated activity in “embodied” sensorimotor systems underlies the formation of memory traces, why should memory cells emerge in areas distant from their antecedent activations in sensorimotor areas, thus leading to “disembodiment” (movement away from sensorimotor systems) of memory mechanisms? We modelled the formation of memory circuits in six-area neurocomputational architectures, implementing motor and sensory primary, secondary and higher association areas in frontotemporal cortices along with known between-area neuroanatomical connections. Sensorimotor learning driven by Hebbian neuroplasticity led to formation of cell assemblies distributed across the different areas of the network. These action-perception circuits (APCs) ignited fully when stimulated, thus providing a neural basis for long-term memory (LTM) of sensorimotor information linked by learning. Subsequent to ignition, activity vanished rapidly from APC neurons in sensorimotor areas but persisted in those in multimodal prefrontal and temporal areas. Such persistent activity provides a mechanism for working memory for actions, perceptions and symbols, including short-term phonological and semantic storage. Cell assembly ignition and “disembodied” working memory retreat of activity to multimodal areas are documented in the neurocomputational models' activity dynamics, at the level of single cells, circuits, and cortical areas. Memory disembodiment is explained neuromechanistically by APC formation and structural neuroanatomical features of the model networks, especially the central role of multimodal prefrontal and temporal cortices in bridging between sensory and motor areas. These simulations answer the “where” question of cortical working memory in terms of distributed APCs and their inner structure, which is, in part, determined by neuroanatomical structure. As the neurocomputational model provides a mechanistic explanation of how memory-related “disembodied” neuronal activity emerges in “embodied” APCs, it may be key to solving aspects of the embodiment debate and eventually to a better understanding of cognitive brain functions