Terms Of Brain Function Research Articles

FMRI study of effort and information processing in a working memory task

It is unclear how effort translates into brain function. In this study we endeavored to identify the activity in a working memory task that is related to the allocation of mental resources. Such activity, if present, would be a likely candidate to explain how effort works in terms of brain function. Eleven healthy participants performed a Sternberg task with a memory-set of one, three, or five consonants in an fMRI study. Probe stimuli were either one consonant or one digit. We expected digits to be processed automatically and consonants to require working memory. Because the probe type was unpredictable and subjects had to respond as fast as possible, we expected subjects to allocate mental resources on the basis of the memory-set size, not the probe type. Accordingly, we anticipated that activity in regions involved in effort would be a function of the size of the memory-set, but independent of the type of probe. We found that the reaction-time for digits increased in line with our expectation of automatic processing and the reaction time for letters increased in line with our expectation of controlled processing. fMRI revealed that activity in the right ventral-prefrontal cortex changed as a function of effort. The ventral anterior cingulate cortex and hypothalamus showed reduced activity as a function of effort. Activity in regions regarded as pivotal for working memory (among others, the left dorsolateral prefrontal cortex, anterior cingulate cortex) appeared to be predominantly related to information processing and not involved in effort.

Intrinsic brain activity sets the stage for expression of motivated behavior

Research in many species has provided increasingly detailed information on relevant, primarily subcortical brain systems supporting the expression of basic appetites and drives. While basic appetites and drives are essential for adaptation and survival in any environment, they are naturally constrained by an organism's inherent biology and modulated as circumstances dictate. The brain mechanisms which serve to constrain and modulate them, however, remain much less well understood. We suggest that the manner in which such constraint and potential modulation is achieved likely involves processes that emerge from the coordinated behavior of multiple brain systems, and functional brain imaging techniques such as PET and fMRI are beginning to help us understand aspects of such coordination. In this review we argue that, in pursuit of this understanding, we must focus not only on changes evoked in brain systems during various behaviors, but also on the ongoing and very costly intrinsic activity within these systems, for the latter may be at least as important as the evoked activity in terms of brain function in general and the constraint and modulation of basic appetites and drives in particular. Distinguishing intrinsic from evoked activity in the context of functional brain imaging experiments is challenging, however. Here we review some evolving strategies for doing so.

Relating connectional architecture to grey matter function using diffusion imaging

Understanding brain function in terms of connectional architecture is a major goal of neuroimaging. However, direct investigation of the influence of brain circuitry on function has been hindered by the lack of a technique for exploring anatomical connectivity in the in vivo brain. Recent advances in magnetic resonance diffusion imaging have given scientists access to data relating to local white matter architecture and, for the first time, have raised the possibility of in vivo investigations into brain circuitry. This review investigates whether diffusion imaging may be used to identify regions of grey matter that are distinct in their connectional architecture, and whether these connectional differences are reflected either in local cytoarchitecture or in local grey matter function. Establishing a direct relationship between regional boundaries based on diffusion imaging and borders between regions that perform different functions would not only be of great significance when interpreting functional results, but would also provide a first step towards the validation of diffusion-based anatomical connectivity studies.

Diffusive neural network

A non-connectionist model of a neuronal network based on passive diffusion of neurotransmitters is presented as an alternative to hard-wired artificial neural networks. Classic thermodynamical approach shows that the diffusive network is capable of exhibiting asymptotic stability and a dynamics resembling that of a chaotic system. Basic computational capabilities of the net are discussed based on the equivalence with a Turing machine. The model offers a way to represent mass-sustained brain functions in terms of recurrent behaviors in the phase space.

Effects of nootropic drugs for demented patients—a study using LORETA

To evaluate the efficacy of nootropic drugs on higher brain function in terms of time and space, electrical field distributions of the scalp map and low-resolution electromagnetic tomography (LORETA) were applied for evoked potentials (EPs) and spontaneous eyes-closed EEG. The studies were carried out on demented patients. We examined them before and after the administration of nicotine with a patch and nefiracetam, which is a pyrrolidine derivative agonist. We recorded event-related potentials (ERPs) with auditory “oddball” paradigm, auditory middle latency response (MLR) and spontaneous eyes-closed resting EEG. Multichannel EPs and EEG data were measured and averaged using a Biologic Brain Atlas. LORETA was used to compute the three-dimensional intracerebral distribution of electric activity of the EPs and the EEG frequency bands. Psychological examinations were also performed. After treatment with nefiracetam, the potential distribution of P3 differed clearly between before and after the administration. This change showed improvement towards normal values. For nicotine, significant effects were found in the MLR P1 component and in some EEG frequency bands. In addition, LORETA for EEG indicated inhibitory, normal and excitatory activity. These findings were supported by significant improvements of the performance test. We conclude that the spatial distribution of inhibitory, normal and excitatory activity, obtained from multichannel EPs and EEG data, allows the assessment of the complex effect of nootropic drugs.

Erythropoietin therapy in chronic uremia: the impact of normalization of hematocrit.

The target hematocrit to be achieved when treating anemia in hemodialysis patients with erythropoietin is controversial. Current evidence-based recommendations suggest a target hematocrit range of 33% to 36%. Small studies suggest that normalization of hematocrit with erythropoietin may benefit hemodialysis patients in terms of brain function, physical performance, quality of life, and prevention of progressive left ventricular dilatation. However a recent study of the effects of erythropoietin-induced normalization of hematocrit in hemodialysis patients with symptomatic heart disease has shown an increase in both mortality and the rate of vascular access thrombosis. Currently, normalization of hematocrit in patients with symptomatic heart disease is not recommended, nor is it possible to conclude that possible benefits of normalization of hematocrit will outweigh risks in hemodialysis patients without symptomatic heart disease.

Human organ transplantation: background and consequences.

The story of the renal transplant program of the Peter Bent Brigham Hospital (now the Brigham and Women's Hospital) in Boston weaves together three distinct threads: the study of renal disease, the phenomenon of skin grafting in twins, and the development of surgical procedures ultimately leading to the use of chemical immunosuppression. The common leitmotiv is one of a single event or report proving to be decisive. Unanticipated consequences of successful human organ transplantation include the reorganization of clinical and nonclinical disciplines, national and international cooperation in organ preservation and distribution, tissue-typing as a marker for disease, redefinition of death in terms of brain function, better understanding of disease processes, and new health care quandaries that result from the scarcity of organ donors.

The effects of extreme hemodilutions on the autoregulation of cerebral blood flow, electroencephalogram and cerebral metabolic rate of oxygen in the dog.

The effects of profound (hematocrit value, Ht 20%) and extreme (Ht 5%) hemodilutions on the relationship between the mean arterial pressure (MAP) and the cerebral blood flow (CBF) were studied in pentobarbital-anesthetized dogs. A regression line was found between the CBF and Ht values during normotensive hemodilution (MAP 100 torr): CBF (ml/100g X min) = -98.9 log Ht (%) + 195.5 (p less than 0.001). The CBF was increased by hemodilution, but the range of its autoregulation was narrowed, suggesting a progressive susceptibility of CBF to blood pressure with hemodilution. The electroencephalogram (EEG) was not significantly changed by hemodilution within the range of the CBF autoregulation, below which it became slowed. In contrast, the cerebral metabolic rate of oxygen (CMRo2) was decreased by hemodilution even within the range of the CBF autoregulation, while there were no significant differences in CMRo2 values between MAPs of 100 and 40 torr. Thus, the brain function in terms of the EEG seemed to correlate more with the autoregulatory mechanism of the CBF than with the CMRo2 value in the hemodiluted states.

Computer models and the brain

Psychologists and computer enthusiasts have talked at length about the relationships between processing of information by the brain and processing of information by the computer. Models relating the two have been suggested, and attempts to draw analogies between the methods in which a computer would do a task and how the brain works have been frequent. Indeed, it has become popular to discuss brain functions in terms of computer terminology, and to project to the time when computers will duplicate brain processes. The present article discusses some of the difficulties and misassumptions which can arise from such discussions, and discusses those issues which must be addressed by those who wish to use the computer as a substitute for the brain.

A model of human associative processor (HASP)

A model of an associative processor names HASP is proposed and described. The objective is to represent associative brain functions in terms of neural network structure. HASP is described with emphasis on its associative memory functions. HASP solved two critical problems which resided in earlier associative memory models: crosstalk noise elimination and multiple-match resolution. HASP eliminates crosstalk noise without complicated orthogonalizing methods. Both problems are solved by the same network structure. With the function of crosstalk noise elimination, the storage capacity increases, and an explosion of crosstalk noise, inevitable in a system such as mutually linked associative networks, can be avoided. With the function of multiple-match resolution, various operations of retrieving information from a memory organized in complicated data structures are possible.

The effect of methadone on fetal brain function

The effect of methadone on fetal brain function in terms of the electroencephalogram (EEG) was studied in eight short-term fetal sheep experiments by single injections of 5 to 20 mg. of methadone into the fetal circulation. Plasma methadeone concentrations (determined by radioimmunoassay) greater than 0.065 mg. per cent were associated with an immediate brief decrease in carotid blood flow, a rapid decrease in frequency and amplitude in the EEG that occasionally became isoelectric but recovered, and immediate and relatively prolonged bradycardia. Similar cardiovascular observations were obtained with plasma methadone concentrations less than 0.065 mg. per cent, but the EEG changes were either minimal or not observed. These results indicate that uptake of methadone by the fetal brain is rapid and that electrical activity and heart rate are affected.

The effect of hypoglycemia on fetal brain function and metabolism

The effect of hypoglycemia on brain function in terms of the electroencephalogram (EEG) and on brain metabolism in terms of arteriovenous differences in substrate concentrations was studied in 11 in utero fetal sheep experiments. Fetal hypoglycemia was induced by an infusion of insulin to the ewe that resulted in maternal hypoglycemia. Carotid artery glucose concentration decreased to values that were 25 per cent of base line and as low as 3 mg. per 100 ml. The peak effect occurred 30 to 50 minutes following insulin infusion. The fetal EEG showed only minimal changes that consisted of a decrease in voltage and slowing on occasion. A significant decrease in heart rate occurred during the hypoglycemia. There was no significant change in oxygen consumption, blood flow, pH, or PCO2. A significant reduction (p < 0.005) occurred in the arteriovenous difference of both glucose and glucose consumption. The ratio of glucose to oxygen utilization was also significantly reduced (p < 0.01). There was no significant difference in the metabolism of lactate, pyruvate, and free fatty acids which suggests other undefined substrate utilization during hypoglycemia.

Linear analysis of the dynamics of neural masses.

Walter J. Freeman Journal Article e–Reprint Reprinted from ANNUAL REVIEW OF BIOPHYSICS AND BIOENGINEERING, Vol. 1, 1972 This work was supported by NIMH Grant MH 06686. cc: CREATIVE COMMONS COPYRIGHT: Attribution-Share alike Licence Original PDF File Source: http://sulcus.berkeley.edu/FreemanWWW/manuscripts/IA3/72.html This review is concerned with the problem of how to identify and characterize masses of neurons empirically as dynamic entities that have properties related to but distinct from those of the component neurons. This can only be done by observing and measuring experimentally the responses of neural masses to known stimuli. But measurement presupposes some theoretical framework to provide the necessary basis functions and the units. For example, a value for frequency is predicated on the presence of a periodic wave-form; a rate constant presumes an exponential decay; a numerical estimate of dispersion requires some distribution function; and so forth. The purpose of this review is to suggest that linear systems analysis can provide a very useful structure for measuring compound neural responses and for comprehending some of the elementary underlying dynamics. It does not define the entities nor explain what they do or how they do it. It merely provides the basis for measurement, which is the first step beyond uncorrelated observations and the prerequisite for testing theories of neural masses. WHAT IS A NEURAL MASS? Granted that nervous systems are composed of neurons, the most compelling fact about even the simpler brains is that the numbers of neurons are extremely large. Because the neuron is conceived as the elementary unit of neural function, and because it is accessible to measurement by an array of microtechniques, the proper aim of neurophysiology is the analysis of brain function in terms of the properties of single neurons. Yet most of what is known about the operation of the brain in relation to behavior has come from studies based on stimulation (electrical or chemical), field potential recordings, or ablation (by selective surgery or disease) of masses of brain tissue containing tens or hundreds of millions of neurons. The conceptual gap between the functions of single neurons and those numbers of neurons is still very wide.

The Neurological Evaluation of School-Age Children

The field of learning disabilities is literally forcing many disciplines to re-evaluate present testing and screening instruments. In this abstract, Dr. Ozer is offering a preliminary communication describing an approach that his facility is taking to devise an accurate and prompt neurological examination. It is propitious for the field of learning disabilities that neurology is attempting to measure brain function in terms of rate of learning. The Journal is looking forward to a future report from Dr. Ozer and we would suggest all interested persons make application to him for copies of the forms and instructions that he is using for this evaluation technique.—C. C. E.