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PubMed1983

Imprinting and cortical plasticity: a comparative review.

Results of research on imprinting and developmental neurobiology of the visual cortex are compared to evaluate the evidence for or against a frequently hypothesized linkage of the two phenomena. The comparison reveals striking similarities. In both paradigms a sensitive period exists. Once this sensitive period is over, the storage of early influences from the environment remains stable throughout life. Storage of "natural" stimuli is facilitated by a certain preorganisation of the receiving brain areas. It is stated that the two phenomena are not directly linked, but are two expressions of a developmental process, which may be common for the organisation of the connectivity of single cells as well as for complex neuronal networks as they are likely to be involved in imprinting. This process is basically self-organizing, but can be influenced by superimposed controls. Differences of the stability of storage of external influences might be explained by the difference in the overall amount of morphological alterations, which is large in the young and small in the adult animal. This holds for both the modifiability in the visual cortex and imprinting.

Age Factors↗

PubMed1998

Anatomical interrelationships of the medial preoptic area and other brain regions activated following male sexual behavior: a combined fos and tract-tracing study.

The medial preoptic nucleus (MPN) is an essential site for the regulation of male sexual behavior. Previous studies using c-fos as a marker for neural activation have shown that copulation increased c-fos expression in the MPN. Neural activation was also present in brain regions that are connected with the MPN and are involved in male sexual behavior, including the posteromedial bed nucleus of the stria terminalis (BNSTpm), posterodorsal preoptic nucleus (PD), posterodorsal medial amygdala (MEApd), and parvocellular subparafascicular thalamic nucleus (SPFp). The present study investigated whether the copulation-induced, activated neurons in these brain regions are involved in the bidirectional connections with the MPN. Therefore, mating-induced Fos expression was combined with application of anterograde (biotinylated dextran amine) or retrograde (cholera toxin B subunit) tracers in the MPN. The results demonstrated that neurons in the BNSTpm, PD, MEApd, and SPFp that project to the MPN were activated following copulation. However, in males that displayed sexual behavior but did not achieve ejaculation, few double-labeled neurons were evident, although both retrogradely labeled neurons and Fos-immunoreactive cells were present. In addition, retrograde neurons that expressed Fos were located in discrete subdivisions within the brain regions studied, where Fos is induced after ejaculation. Likewise, anterogradely labeled fibers originating from the MPN were not distributed homogeneously but were particularly dense in these discrete subdivisions. These results demonstrate that copulation-induced Fos-positive neurons in specific subdivisions of the BNSTpm, PD, MEApd, and SPFp have bidirectional connections with the MPN. Taken together with previous findings, this supports the existence of a discrete subcircuit within a larger neural network underlying male sexual behavior.

Afferent Pathways↗

PubMed2004

Cerebral modeling and dynamic Bayesian networks.

The understanding and the prediction of the clinical outcomes of focal or degenerative cerebral lesions, as well as the assessment of rehabilitation procedures, necessitate knowing the cerebral substratum of cognitive or sensorimotor functions. This is achieved by activation studies, where subjects are asked to perform a specific task while data of their brain functioning are obtained through functional neuroimaging techniques. Such studies, as well as animal experiments, have shown that sensorimotor or cognitive functions are the offspring of the activity of large-scale networks of anatomically connected cerebral regions. However, no one-to-one correspondence between activated networks adn functions can be found. Our research aims at understanding how the activation of large-scale networks derives from cerebral information processing mechanisms, which can only explain apparently conflicting activation data. Our work falls at the crossroads of neuroimaging interpretation techniques and computational neuroscience. Since knowledge in cognitive neuroscience is permanently evolving, our research aims more precisely at defining a new modeling formalism and at building a flexible simulator, allowing a quick implementation of the models, for a better interpretation of cerebral functional images. It also aims at providing plausible models, at eht level of large-scale networks, of cerebral information processing mechanisms in humans. In this paper, we propose a formalism, based on dynamic Bayesian networks (DBNs), that respects the following constraints: an oriented, networks architecture, whose nodes (the cerebral structures) can all be different, the implementation of causality--the activation of the structure is caused by upstream nodes' activation--the explicit representation of different time scales (from 1 ms for the cerebral activity to many seconds for a PET scan image acquisition), the representation of cerebral information at the integrated level of neuronal populations, the imprecision of functional neuroimaging data, the nonlinearity and the uncertainty in cerebral mechanisms, and brain's plasticity (learning, reorganization, modulation). One of the main problems, nonlinearity, has been tackled thanks to new extensions of the Kalman filter. The capabilities of the formalism's current version are illustrated by the modeling of a phoneme categorization process, explaining the different cerebral activations in normal and dyslexic subjects.

Bayes Theorem↗

PubMed2005

Oculomotor studies of cerebellar function in autism.

Histopathological, neuroimaging and genetic findings indicate cerebellar abnormalities in autism, but the extent of neurophysiological dysfunction associated with those findings has not been systematically examined. Suppression of intrusive saccades (square wave jerks) and the ability to sustain eccentric gaze, two phenomena requiring intact cerebellar function, were examined in 52 high-functioning individuals with autism and 52 age- and IQ-matched healthy subjects during visual fixation of static central and peripheral targets. Rates of intrusive saccades were not increased in autism during visual fixation, and foveopetal ocular drift was also not increased when subjects held an eccentric gaze. The absence of gross disturbances of visual fixation associated with cerebellar disease in individuals with autism, such as increased square wave jerk rates and foveopetal drift when holding eccentric gaze, indicates that the functional integrity of cerebellar--brainstem networks devoted to oculomotor control is preserved in autism despite reported anatomic variations. However, increased amplitude of intrusive saccades and reduced latency of target refixation after intrusive saccades were observed in individuals with autism, especially when subjects maintained fixation of remembered target locations without sensory guidance. The atypical metrics of intrusive saccades that were observed may be attributable to faulty functional connectivity in cortico-cerebellar networks.

Adolescent↗

PubMed2000

Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research.

Artificial neural networks (ANNs) are biologically inspired computer programs designed to simulate the way in which the human brain processes information. ANNs gather their knowledge by detecting the patterns and relationships in data and learn (or are trained) through experience, not from programming. An ANN is formed from hundreds of single units, artificial neurons or processing elements (PE), connected with coefficients (weights), which constitute the neural structure and are organised in layers. The power of neural computations comes from connecting neurons in a network. Each PE has weighted inputs, transfer function and one output. The behavior of a neural network is determined by the transfer functions of its neurons, by the learning rule, and by the architecture itself. The weights are the adjustable parameters and, in that sense, a neural network is a parameterized system. The weighed sum of the inputs constitutes the activation of the neuron. The activation signal is passed through transfer function to produce a single output of the neuron. Transfer function introduces non-linearity to the network. During training, the inter-unit connections are optimized until the error in predictions is minimized and the network reaches the specified level of accuracy. Once the network is trained and tested it can be given new input information to predict the output. Many types of neural networks have been designed already and new ones are invented every week but all can be described by the transfer functions of their neurons, by the learning rule, and by the connection formula. ANN represents a promising modeling technique, especially for data sets having non-linear relationships which are frequently encountered in pharmaceutical processes. In terms of model specification, artificial neural networks require no knowledge of the data source but, since they often contain many weights that must be estimated, they require large training sets. In addition, ANNs can combine and incorporate both literature-based and experimental data to solve problems. The various applications of ANNs can be summarised into classification or pattern recognition, prediction and modeling. Supervised 'associating networks can be applied in pharmaceutical fields as an alternative to conventional response surface methodology. Unsupervised feature-extracting networks represent an alternative to principal component analysis. Non-adaptive unsupervised networks are able to reconstruct their patterns when presented with noisy samples and can be used for image recognition. The potential applications of ANN methodology in the pharmaceutical sciences range from interpretation of analytical data, drug and dosage form design through biopharmacy to clinical pharmacy.

Algorithms↗

PubMed2005

Effects of inhibitory feedback in a network model of avian brain stem.

The avian auditory brain stem consists of a network of specialized nuclei, including nucleus laminaris (NL) and superior olivary nucleus (SON). NL cells show sensitivity to interaural time difference (ITD), a critical cue that underlies spatial hearing. SON cells provide inhibitory feedback to the rest of the network. Empirical data suggest that feedback inhibition from SON could increase the ITD sensitivity of NL across sound level. Using a bilateral network model, we assess the effects of SON feedback inhibition. Individual cells are specified as modified leaky-integrate-and-fire neurons with time constants and thresholds that vary with inhibitory input. Acoustic sound level is reflected in the discharge rates of the model auditory-nerve fibers, which innervate the network. Simulations show that with SON inhibitory feedback, ITD sensitivity is maintained in model NL cells over a threefold range in auditory-nerve discharge rate. In contrast, without SON feedback inhibition, ITD sensitivity is significantly reduced as input rates are increased. Feedback inhibition is most beneficial in maintaining ITD sensitivity at high-input rates (simulating high sound levels). With SON inhibition, ITD sensitivity is maintained for both interaurally balanced inputs (simulating an on-center sound source) and interaurally imbalanced inputs (simulating a lateralized source). Further, the empirically observed temporal build-up of SON inhibition and the presence of reciprocal inhibitory connections between the ipsi- and contralateral SON both improve ITD sensitivity. In sum, our network model shows that inhibitory feedback can substantially increase the sensitivity and dynamic range of ITD coding in the avian auditory brain stem.

Action Potentials↗

PubMed2006

Tracking the states of a nonlinear and nonstationary system in the weight-space of artificial neural networks.

We propose a novel interpretation and usage of Neural Network (NN) in modeling physiological signals, which are allowed to be nonlinear and/or nonstationary. The method consists of training a NN for the k-step prediction of a physiological signal, and then examining the connection-weight-space (CWS) of the NN to extract information about the signal generator mechanism. We define a novel feature, Normalized Vector Separation (gamma(ij)), to measure the separation of two arbitrary states "i" and "j" in the CWS and use it to track the state changes of the generating system. The performance of the method is examined via synthetic signals and clinical EEG. Synthetic data indicates that gamma(ij) can track the system down to a SNR of 3.5 dB. Clinical data obtained from three patients undergoing carotid endarterectomy of the brain showed that EEG could be modeled (within a root-means-squared-error of 0.01) by the proposed method, and the blood perfusion state of the brain could be monitored via gamma(ij), with small NNs having no more than 21 connection weight altogether.

Brain Ischemia↗

PubMed2004

Changing patterns of brain activation during category learning revealed by functional MRI.

Functional magnetic resonance imaging (fMRI) was used to investigate neural changes as a function of category learning in normals (n=8). Subjects were trained to classify patterns of dots into four categories over 4 consecutive days. fMRI monitored the changes that occurred during learning prior to training and then following each training session. During fMRI, subjects determined whether two patterns of dots were members of the same category. The behavioral changes that occurred as a result of the training were observed as increases in response accuracy within shortened response times. fMRI illustrated initial increases in volumes of activation distributed across the known visuospatial processing networks. The regions affected by learning were identified as those involved in the planning and execution of eye movements (frontal and supplementary eye fields, FEF and SEF), spatial attention (superior and inferior parietal lobules, SPL and IPL) and visual processing (primary, secondary, and tertiary visual cortices). The volumes of activation then decreased as training progressed further. Of the two proposed mechanisms for learning, that of strengthened connectivity on a given network and that of selection of different networks, our data supports the former.

Adult↗

PubMed1986

Kindling model of epilepsy.

Kindling is an animal model of epilepsy produced by focal electrical stimulation of the brain. This chapter: describes the kindling phenomenon; considers the validity of kindling as an animal model and proposes a hypothesis as to how kindling might contribute to human epileptogenesis; presents a critical review of current insights into the underlying mechanisms; and emphasizes that, if progress is to be made in understanding the mechanisms, the network of brain structures underlying kindling must be elucidated. Recent investigations directly related to the network issue are considered, namely studies demonstrating that a brainstem structure, the substantia nigra (SN), can regulate the kindled seizure threshold. Thus, either microinjection of a GABA receptor agonist or a GABA transaminase inhibitor into SN, but not into nearby sites, elevates kindled-seizure threshold. Likewise, destruction of SN, but not of adjacent structures, is associated with an increase of kindled-seizure threshold. These treatments suppress not only clonic motor seizures, but also complex partial seizures and afterdischarge at the site of stimulation. These findings demonstrate that the SN can regulate the intrinsic neuronal excitability of forebrain structures. A hypothesis is advanced that generation of a complex partial seizure requires activation of neurons in the SN which in turn feed back through polysynaptic connections to influence neurons at the site of seizure origin. This nigral influence on neurons at the site of seizure origin is either a direct excitation or a disinhibition. Thus, the seizure represents reverberatory activity within a network of brain structures which includes the SN. Other investigators have proposed that the centrencephalic system subserved seizure propagation; the relationship of the hypothesis proposed here to these earlier ideas is discussed.

Animals↗

PubMed2006

Using a speech perception neural network computer simulation to contrast neuroanatomic versus neuromodulatory models of auditory hallucinations.

A number of studies suggest that schizophrenia may arise from overzealous pruning of synapses that are an extension of normal developmental pruning during adolescence. Moreover, there has been a long history of studies suggesting that this disorder arises from alterations in the dopaminergic neuromodulatory systems. In order to further assess and compare these two hypotheses, a computer simulation of some aspects of speech perception was developed utilizing a recurrent, backpropagation model of working memory previously reported by Elman . This system was found to produce spontaneous percepts simulating hallucinated speech when the working memory component either was excessively pruned or when neuronal responses were modulated to simulatea hyperdopaminergic system. These hallucinogenic systems also demonstrated disruptions in processing input information when "phonetic information" was degraded. The perceptual performance of these systems were compared to that of actual hallucinating patients and normal controls while tracking (repeating while simultaneously listening to) speech that was phonetically degraded. We found that the neural network simulation producing the best match to speech tracking performance of human hallucinators was an overpruned system with compensatory hypodopaminergic adjustments. These data suggest that the primary pathophysiology of schizophrenia arises from curtailed connectivity in working memory systems and that dopaminergic alterations reflect secondary compensatory adjustments.

Adolescent↗

PubMed2004

Plasticity in the human cerebral cortex: lessons from the normal brain and from stroke.

The adult brain maintains the ability for reorganization or plasticity throughout life. Results from neurophysiological and neuroanatomical experiments in animals and noninvasive neuroimaging and electrophysiological studies in humans show considerable plasticity of motor representations with use or nonuse, skill learning, or injury to the nervous system. An important concept of reorganization in the motor cortex is that of a distributed neuronal network in which multiple overlapping motor representations are functionally connected through an extensive horizontal network. By changing the strength of horizontal connections between motor neurons, functionally different neuronal assemblies can form, thereby providing a substrate to construct dynamic motor output zones. Modulation of inhibition and synaptic efficacy are mechanisms involved. Recent evidence from animal experiments indicates that these functional changes are accompanied by anatomical changes. Because plasticity of the brain plays a major role in the recovery of function after stroke, the knowledge of the principles of plasticity may help to design strategies to enhance plasticity when it is beneficial, such as after brain infarction.

Animals↗

PubMed2004

A long-range cortical network emerging with theta oscillation in a mental task.

Human scalp EEG has demonstrated that global coherence among distant areas increases during cognitive tasks, suggesting that oscillating neural activities work to generate global neuronal assemblies for cognitive functions. The theta oscillation in a frequency range of 4-8 Hz with large amplitudes which emerges during mental tasks around the frontal midline region is called fm theta. If theta oscillation concerns the global neuronal assemblies, fm theta should be associated with regional activities that depend on task conditions. In the present study, we examine the EEG-related brain activities by developing simultaneous EEG and fMRI during a mental calculation task. EEG-related negative BOLD was dominant over anterior medial regions, suggesting a major contribution of negative BOLD to fm theta. Negative and positive BOLD were found over distant regions. Functional connectivity analyses revealed that the connectivity varied remarkably according to mental conditions. In the rest condition, the connectivity was localized, whereas in the task condition, a long-range coherent network was formed by the anterior midline, posterior cingulate and right middle temporal cortices with linking between the right middle temporal and left lateral cortices during numerical processing. Further EEG analyses indicate that the long-range coherent network executing cognitive functions is coordinated in the time window of theta oscillations.

Action Potentials↗

PubMed1993

The visual system and levels of perception: properties of neuromental organization.

To see whether the mental and the neural have common attributes that could resolve some of the traditional dichotomies, we review neuroscientific data on the visual system. The results show that neuronal and perceptual function share a parallel and hierarchical architecture which is manifest not only in the anatomy and physiology of the visual system, but also in normal perception and in the deficits caused by lesions in different parts of the system. Based on the description of parallel hierarchical levels of active information processing in the visual brain, we suggest a concept of dissociable levels of perception, advocating that the phenomenal perception and recognition is realized in the functional integrity of a network of reciprocal cortico-cortical connections. The properties shared by neuronal and perceptional functions provide a basis for a neuromental monism in which both functions are attributed a causal role.

Cerebral Cortex↗

PubMed2001

Experience-dependent changes in cerebral functional connectivity during human rapid eye movement sleep.

One function of sleep is hypothesized to be the reprocessing and consolidation of memory traces (Smith, 1995; Gais et al., 2000; McGaugh, 2000; Stickgold et al., 2000). At the cellular level, neuronal reactivations during post-training sleep in animals have been observed in hippocampal (Wilson and McNaughton, 1994) and cortical (Amzica et al., 1997) neuronal populations. At the systems level, using positron emission tomography, we have recently shown that some brain areas reactivated during rapid-eye-movement sleep in human subjects previously trained on an implicit learning task (a serial reaction time task) (Maquet et al., 2000). These cortical reactivations, located in the left premotor area and bilateral cuneus, were thought to reflect the reprocessing--possibly the consolidation--of memory traces during post-training rapid-eye-movement sleep. Here, the experience-dependent functional connectivity of these brain regions is examined. It is shown that the left premotor cortex is functionally more correlated with the left posterior parietal cortex and bilateral pre-supplementary motor area during rapid-eye-movement sleep of subjects previously trained to the reaction time task compared to rapid-eye-movement sleep of untrained subjects. The increase in functional connectivity during post-training rapid-eye-movement sleep suggests that the brain areas reactivated during post-training rapid-eye-movement sleep participate in the optimization of the network that subtends subject's visuo-motor response. The optimization of this visuo-motor network during sleep could explain the gain in performance observed during the following day.

Brain Mapping↗

PubMed1980

Structure and composition of the cytoskeleton of nucleated erythrocytes I. The presence of microtubule-associated protein 2 in the marginal band.

The marginal band (MB) of nucleated erythrocytes is composed of a bundle of microtubules that encircles the cell immediately beneath the plasma membrane. When cells are lysed in buffer containing Triton X-100 the MB microtubules remain intact, and the nucleus remains suspended at the cell center by a filamentous network called the trans-MB material that connects the nucleus to the peripheral MB. When these lysed cells are prepared for indirect immunofluorescence by use of an antibody to chick brain microtubule-associated protein 2 (MAP 2), intense staining of the MB results; no staining is evident in the areas occupied by the nucleus or the trans-MB material. Controls demonstrate that the staining is specific, because no staining occurs with fluorescent goat antirabbit serum alone or when nonimmune serum is used as the first antibody. Furthermore, the fluorescence of the MB is not affected by pretreatment of the immune serum with purified tubulin, but staining is prevented by pretreatment of the immune serum with purified MAP 2. To determine which protein component of the MB was responsible for the positive immunofluorescence results, 125I-protein A staining was used after the protein components of the isolated cytoskeleton had been resolved by SDS-polyacrylamide gels. Controls showed that the antiserum could react on SDS gels with MAP 2 from purified chick brain microtubules. The results with the cytoskeletal proteins demonstrated that the antiserum reacted only with a high molecular weight protein having a molecular weight similar, but not identical, to that of chick brain MAP 2. Thus, it is concluded that a protein with antigenic characteristics similar to those of chick brain MAP 2 is a component of the MB. The results are discussed in terms of the possible function of MAP 2 in the MB.

Animals↗

PubMed1994

Component placement optimization in the brain.

This computational neuroanatomy study evaluates how well some formalisms derived from combinatorial network optimization theory fit as models for brain structure. At multiple hierarchical levels--brain, ganglion, individual cell--physical placement of neural components appears consistent with a single, simple goal: minimize cost of connections among the components. The most dramatic instance of this "save wire" organizing principle is reported for adjacencies among ganglia in the nematode nervous system; among about 40,000,000 alternative layout orderings, the actual ganglion placement in fact requires the least total connection length. In addition, evidence supports a component placement optimization hypothesis for positioning of individual neurons in the nematode, and also for positioning of mammalian cortical areas.

Adult↗

PubMed2004

Perinidal dilated capillary networks in cerebral arteriovenous malformations.

OBJECTIVE: The perinidal vascular structures of cerebral arteriovenous malformations were examined, to clarify their pathomorphological features. METHODS: Twenty-two resected specimens of human brain structures adjacent to the nidus were examined. The vessels surrounding the nidus were three-dimensionally reconstructed with a computer graphics system. RESULTS: In all cases, the analysis of serial sections revealed that perinidal dilated capillaries were located in brain tissue 1 to 7 mm from the nidal border. The vessels surrounding the nidus demonstrated markedly dilated capillary networks (perinidal dilated capillary network [PDCN]). The diameters of the vessels forming the PDCN were 10 to 25 times those of normal capillaries. The PDCN connected not only to the nidus, feeding arteries, and draining veins, via arterioles and venules, but also to the normal capillary network, arterioles, and venules. CONCLUSION: Without exception, each nidus was accompanied by a PDCN, which connected not only to the nidus, feeding arteries, and draining veins, via arterioles and venules, but also to normal capillaries, arterioles, and venules. The PDCN should be considered in studies aimed at gaining an understanding of the mechanisms underlying the intraoperative and postoperative bleeding, growth, and recurrence of surgically treated cerebral arteriovenous malformations.

Adolescent↗

PubMed2000

Anatomical connectivity defines the organization of clusters of cortical areas in the macaque monkey and the cat.

The number of different cortical structures in mammalian brains and the number of extrinsic fibres linking these regions are both large. As with any complex system, systematic analysis is required to draw reliable conclusions about the organization of the complex neural networks comprising these numerous elements. One aspect of organization that has long been suspected is that cortical networks are organized into 'streams' or 'systems'. Here we report computational analyses capable of showing whether clusters of strongly interconnected areas are aspects of the global organization of cortical systems in macaque and cat. We used two different approaches to analyse compilations of corticocortical connection data from the macaque and the cat. The first approach, optimal set analysis, employed an explicit definition of a neural 'system' or 'stream', which was based on differential connectivity. We defined a two-component cost function that described the cost of the global cluster arrangement of areas in terms of the areas' connectivity within and between candidate clusters. Optimal cluster arrangements of cortical areas were then selected computationally from the very many possible arrangements, using an evolutionary optimization algorithm. The second approach, non-parametric cluster analysis (NPCA), grouped cortical areas on the basis of their proximity in multidimensional scaling representations. We used non-metric multidimensional scaling to represent the cortical connectivity structures metrically in two and five dimensions. NPCA then analysed these representations to determine the nature of the clusters for a wide range of different cluster shape parameters. The results from both approaches largely agreed. They showed that macaque and cat cortices are organized into densely intra-connected clusters of areas, and identified the constituent members of the clusters. These clusters reflected functionally specialized sets of cortical areas, suggesting that structure and function are closely linked at this gross, systems level.

Algorithms↗