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The cellular biology of brains is relatively well-understood, but neuroscientists have not yet generated a theory explaining how brains work. Explanations of how neurons collectively operate to produce what brains can do are tentative and incomplete. Without prior assumptions about the brain mechanisms, I attempt here to identify major obstacles to progress in neuroscientific understanding of brains and central nervous systems. Most of the obstacles to our understanding are conceptual. Neuroscience lacks concepts and models rooted in experimental results explaining how neurons interact at all scales. The cerebral cortex is thought to control awake activities, which contrasts with recent experimental results. There is ambiguity distinguishing task-related brain activities from spontaneous activities and organized intrinsic activities. Brains are regarded as driven by external and internal stimuli in contrast to their considerable autonomy. Experimental results are explained by sensory inputs, behavior, and psychological concepts. Time and space are regarded as mutually independent variables for spiking, post-synaptic events, and other measured variables, in contrast to experimental results. Dynamical systems theory and models describing evolution of variables with time as the independent variable are insufficient to account for central nervous system activities. Spatial dynamics may be a practical solution. The general hypothesis that measurements of changes in fundamental brain variables, action potentials, transmitter releases, post-synaptic transmembrane currents, etc., propagating in central nervous systems reveal how they work, carries no additional assumptions. Combinations of current techniques could reveal many aspects of spatial dynamics of spiking, post-synaptic processing, and plasticity in insects and rodents to start with. But problems defining baseline and reference conditions hinder interpretations of the results. Furthermore, the facts that pooling and averaging of data destroy their underlying dynamics imply that single-trial designs and statistics are necessary. [ABSTRACT FROM AUTHOR]

Recent physiological evidence shows that in response to stimuli and preceding motor activity, large fields of the upper layers of the cerebral cortex depolarize. It is argued that this finding is a general one and that these dynamic depolarization fields represent the computational elements of the cerebral cortex. Each depolarization field engages many more neurons than do columns and hyper-columns. These fields can be explained by cooperative neuronal computing in layers I-III of the cortex. In these layers, the computing modes might be general for all parts of the cerebral cortex and be sufficiently flexible to handle all sorts of cortical computations, including perception, memory storage, memory retrieval, thought and the production of behavior.

Sharing scientific data containing complex information requires new concepts and new technology. NEUROGENERATOR is a database generator for the neuroimaging community. A database generator is a database that generates new databases. The scientists submit raw PET and fMRI data to NEUROGENERATOR, which then processes the data in a uniform way to create databases of homogenous data suitable for data sharing, met-analysis and modelling the human brain at the systems level. These databases are then distributed to the scientists.

Brain dynamics are often taken to be temporal dynamics of spiking and membrane potentials in a balanced network. Almost all evidence for a balanced network comes from recordings of cell bodies of few single neurons, neglecting more than 99% of the cortical network. We examined the space-time dynamics of excitation and inhibition simultaneously in dendrites and axons over four visual areas of ferrets exposed to visual scenes with stationary and moving objects. The visual stimuli broke the tight balance between excitation and inhibition such that the network exhibited longer episodes of net excitation subsequently balanced by net inhibition, in contrast to a balanced network. Locally in all four areas the amount of net inhibition matched the amount of net excitation with a delay of 125 ms. The space-time dynamics of excitation-inhibition evolved to reduce the complexity of neuron interactions over the whole network to a flow on a low-(3)-dimensional manifold within 80 ms. In contrast to the pure temporal dynamics, the low dimensional flow evolved to distinguish the simple visual scenes. [ABSTRACT FROM AUTHOR]

Most neurons have a threshold separating the silent non-spiking state and the state of producing temporal sequences of spikes. But neurons in vivo also have a second threshold, found recently in granular layer neurons of the primary visual cortex, separating spontaneous ongoing spiking from visually evoked spiking driven by sharp transients. Here we examine whether this second threshold exists outside the granular layer and examine details of transitions between spiking states in ferrets exposed to moving objects. We found the second threshold, separating spiking states evoked by stationary and moving visual stimuli from the spontaneous ongoing spiking state, in all layers and zones of areas 17 and 18 indicating that the second threshold is a property of the network. Spontaneous and evoked spiking, thus can easily be distinguished. In addition, the trajectories of spontaneous ongoing states were slow, frequently changing direction. In single trials, sharp as well as smooth and slow transients transform the trajectories to be outward directed, fast and crossing the threshold to become evoked. Although the speeds of the evolution of the evoked states differ, the same domain of the state space is explored indicating uniformity of the evoked states. All evoked states return to the spontaneous evoked spiking state as in a typical mono-stable dynamical system. In single trials, neither the original spiking rates, nor the temporal evolution in state space could distinguish simple visual scenes. [ABSTRACT FROM AUTHOR]

Neurons in the primary visual cortex spontaneously spike even when there are no visual stimuli. It is unknown whether the spiking evoked by visual stimuli is just a modification of the spontaneous ongoing cortical spiking dynamics or whether the spontaneous spiking state disappears and is replaced by evoked spiking. This study of laminar recordings of spontaneous spiking and visually evoked spiking of neurons in the ferret primary visual cortex shows that the spiking dynamics does not change: the spontaneous spiking as well as evoked spiking is controlled by a stable and persisting fixed point attractor. Its existence guarantees that evoked spiking return to the spontaneous state. However, the spontaneous ongoing spiking state and the visual evoked spiking states are qualitatively different and are separated by a threshold (separatrix). The functional advantage of this organization is that it avoids the need for a system reorganization following visual stimulation, and impedes the transition of spontaneous spiking to evoked spiking and the propagation of spontaneous spiking from layer 4 to layers 2-3. [ABSTRACT FROM AUTHOR]

A major goal of neuroscience is to reveal mechanisms supporting collaborative actions of neurons in local and larger-scale networks. However, no clear overall principle of operation has emerged despite decades-long experimental efforts. Here, we used an unbiased method to extract and identify the dynamics of local postsynaptic network states contained in the cortical field potential. Field potentials were recorded by depth electrodes targeting a wide selection of cortical regions during spontaneous activities, and sensory, motor, and cognitive experimental tasks. Despite different architectures and different activities, all local cortical networks generated the same type of dynamic confined to one region only of state space. Surprisingly, within this region, state trajectories expanded and contracted continuously during all brain activities and generated a single expansion followed by a contraction in a single trial. This behavior deviates from known attractors and attractor networks. The state-space contractions of particular subsets of brain regions cross-correlated during perceptive, motor, and cognitive tasks. Our results imply that the cortex does not need to change its dynamic to shift between different activities, making task-switching inherent in the dynamic of collective cortical operations. Our results provide a mathematically described general explanation of local and larger scale cortical dynamic. [ABSTRACT FROM AUTHOR]

Visual stimuli of short duration seem to persist longer after the stimulus offset than stimuli of longer duration. This visual persistence must have a physiological explanation. In ferrets exposed to stimuli of different durations we measured the relative changes in the membrane potentials with a voltage sensitive dye and the action potentials of populations of neurons in the upper layers of areas 17 and 18. For durations less than 100 ms, the timing and amplitude of the firing and membrane potentials showed several non-linear effects. The ON response became truncated, the OFF response progressively reduced, and the timing of the OFF responses progressively delayed the shorter the stimulus duration. The offset of the stimulus elicited a sudden and strong negativity in the time derivative of the dye signal. All these non-linearities could be explained by the stimulus offset inducing a sudden inhibition in layers II-III as indicated by the strongly negative time derivative of the dye signal. Despite the non-linear behavior of the layer II-III neurons the sum of the action potentials, integrated from the peak of the ON response to the peak of the OFF response, was almost linearly related to the stimulus duration. [ABSTRACT FROM AUTHOR]

Abstract: Neurons in the visual cortex receive input from the lateral geniculate nucleus (feed-forward), higher order visual areas (feedback) and local neurons in the surroundings (lateral interactions). Here we first briefly review the approximate timing and proportion of these three types of influences on the membrane potentials in visual areas 17, 18 and 19. Then we present original results from an independent component analysis of multiunit spike trains in the same visual areas to resolve the contribution from these three sources. We stimulated the visual cortex of the ferret with a small transient contrast square stimulus and recorded the multiunit activity in areas 17, 18 and 19 with single or multiple electrodes. The spike trains had three reproducible components having their maxima at 40, 55 and 105ms after the start of the presentation of the stimulus. The time course of the third component was significantly correlated with the population membrane potential in the supragranular layers of areas 17, 18 and 19. The first spike train component was interpreted as a feed-forward response, the second spike train component as driving the laterally spreading depolarization and the third spike train component as the firing caused by the lateral spreading- and the feedback depolarization. [Copyright &y& Elsevier]

We have previously shown that motor areas are engaged when subjects experience illusory limb movements elicited by tendon vibration. However, traditionally cytoarchitectonic area 2 is held responsible for kinesthesia. Here we use functional magnetic resonance imaging and cytoarchitectural mapping to examine whether area 2 is engaged in kinesthesia, whether it is engaged bilaterally because area 2 in non-human primates has strong callosal connections, which other areas are active members of the network for kinesthesia, and if there is a dominance for the right hemisphere in kinesthesia as has been suggested. Ten right-handed blindfolded healthy subjects participated. The tendon of the extensor carpi ulnaris muscles of the right or left hand was vibrated at 80 Hz, which elicited illusory palmar flexion in an immobile hand (illusion). As control we applied identical stimuli to the skin over the processus styloideus ulnae, which did not elicit any illusions (vibration). We found robust activations in cortical motor areas [areas 4a, 4p, 6; dorsal premotor cortex (PMD) and bilateral supplementary motor area (SMA)] and ipsilateral cerebellum during kinesthetic illusions (illusion-vibration). The illusions also activated contralateral area 2 and right area 2 was active in common irrespective of illusions of right or left hand. Right areas 44, 45, anterior part of intraparietal region (IP1) and caudo-lateral part of parietal opercular region (OP1), cortex rostral to PMD, anterior insula and superior temporal gyrus were also activated in common during illusions of right or left hand. These right-sided areas were significantly more activated than the corresponding areas in the left hemisphere. The present data, together with our previous results, suggest that human kinesthesia is associated with a network of active brain areas that consists of motor areas, cerebellum, and the right fronto-parietal areas including high-order somatosensory areas. Furthermore, our results provide evidence for a right hemisphere dominance for perception of limb movement. [ABSTRACT FROM AUTHOR]

The somatotopical organization of the postcentral gyrus is well known, but less is known about the somatotopical organization of area 2, the somatosensory association areas in the postparietal cortex, and the parietal operculum. The extent to which these areas are modulated by attention is also poorly understood. For these reasons, we measured the BOLD signal when rectangular parallelepipeds of varying shape were presented to the immobile right hand or right foot of 10 subjects either discriminating these or just being stimulated. Activation areas in each subject were mapped against cytoarchitectural probability maps of area 2, IP1, and IP2 along the intraparietal sulcus and the parietal opercular areas OP1-OP4. In area 2, the somatotopical representation of the hand and foot were distinctly separate, whereas there was considerable overlap in IP1 and no clear evidence of separate representations in OP1, OP4, and IP2. The overlap of hand and foot representations increased in the following order: area 3a, 3b, 1, 2, IP1, OP4, IP2, and OP1. There were significant foot representations but no hand representations in right (ipsilateral) areas 3a, 3b, and 1. Shape discrimination using the foot as opposed to stimulation enhanced the signal in OP4 bilaterally, whereas discrimination with the hand enhanced the signal bilaterally in area 2, IP1, and IP2. These results indicate that somatosensory areas in humans are arranged from strong somatotopy into no somatotopy in the following order: 3a, 3b, 1, 2, IP1, OP4, IP2, and OP1. Higher order areas such as IP1, IP2, and OP4 showed task-related attentional enhancement. [ABSTRACT FROM AUTHOR]

The primary motor cortex (MI) is regarded as the site for motor control. Occasional reports that MI neurons react to sensory stimuli have either been ignored or attributed to guidance of voluntary movements. Here, we show that MI activation is necessary for the somatic perception of movement of our limbs. We made use of an illusion: when the wrist tendon of one hand is vibrated, it is perceived as the hand moving. If the vibrated hand has skin contact with the other hand, it is perceived as both hands bending. Using fMRI and TMS, we show that the activation in MI controlling the nonvibrated hand is compulsory for the somatic perception of the hand movement. This novel function of MI contrasts with its traditional role as the executive locus of voluntary limb movement. [Copyright &y& Elsevier]

In this study we analyzed structural and functional aspects of the human primary somatosensory areas 3a, 3b, and 1 on the basis of a computerized brain atlas. The approach overcomes many of the problems associated with subjective architectonic parcellations of the cortex and with ”classical” brain maps published in a ”rigid” print format. Magnetic resonance (MR) scans were obtained from ten postmortem brains. The brains were serially sectioned at 20 µm, and sections were stained for cell bodies. Areas 3a, 3b, and 1 were delineated statistically on the basis of differences in the laminar densities of neuronal cell bodies. The borders of the areas were topographically variable across different brains and did not match macroanatomical landmarks of the postcentral gyrus. After correction of the sections for deformations due to histological processing, each brain’s 3-D reconstructed histological volume and the volume representations of areas 3a, 3b, and 1 were adapted to the reference brain of a computerized atlas and superimposed in 3-D space. For each area, a population map was generated that described, for each voxel, how many brains had a representation of that area. Despite considerable interindividual variability, representations of areas 3a, 3b, and 1 in ≥50% of the brains were found in the fundus of the central sulcus, in the rostral bank, and on the crown of the postcentral gyrus, respectively. For each area, a volume of interest (VOI) was defined that encompassed that area’s representation in ≥50% of the brains. Despite close spatial relationship in the postcentral gyrus, the three VOIs overlapped by <1% of their volumes. Changes in regional cerebral blood flow (rCBF) were measured with positron emission tomography when six right-handed subjects discriminated differences in the speed of a rotating brush stimulating the palmar surface of the right hand. With co-registered MR images, the rCBF data were adapted to the same reference brain and superimposed with the microstructural VOIs. Discrimination of moving stimuli, contrasted to rest, increased the rCBF in the VOIs of areas 3b and 1, but not in area 3a. This approach opens up the possibility of (1) defining VOIs of cortical areas which are not based on macroanatomical landmarks but instead on observer-independent cytoarchitectonic mapping of postmortem brains and of (2) determining in these VOIs changes in rCBF data obtained from functional imaging experiments. [ABSTRACT FROM AUTHOR]

AbstractThe purpose of this study was to examine the cerebral control of simultaneous movements of the upper and lower limbs. We examined two hypotheses on how the brain coordinates movement: (i) by the involvement of motor representations shared by both limbs; or (ii) by the engagement of specific neural populations. We used positron emission tomography to measure the relative cerebral blood flow in healthy subjects performing isolated cyclic flexion–extension movements of the wrist and ankle (i.e. movements of wrist or ankle alone), and simultaneous movements of the wrist and ankle (a rest condition was also included). The simultaneous movements were performed in the same directions (iso-directional) and in opposite directions (antidirectional). There was no difference in the brain activity between these two patterns of coordination. In several motor-related areas (e.g. the contralateral ventral premotor area, the dorsal premotor area, the supplementary motor area, the parietal operculum and the posterior parietal cortex), the representation of the isolated wrist movement overlapped with the representation of the isolated ankle movement. Importantly, the simultaneous movements activated the same set of motor-related regions that were active during the isolated movements. In the contralateral ventral premotor cortex, dorsal premotor cortex and parietal operculum, there was less activity during the simultaneous movements than for the sum of the activity for the two isolated movements (interaction analysis). Indeed, in the ventral premotor cortex and parietal operculum, the activity was practically identical regardless whether only the wrist, only the ankle, or both the wrist and the ankle were moved. Taken together, these findings suggest that interlimb coordination is mediated by motor representations shared by both limbs, rather than being mediated by specific additional neural populations. [ABSTRACT FROM AUTHOR]

Abstract Illusory contours provide a striking example of the visual system’s ability to extract a meaningful representation of the surroundings from fragmented visual stimuli. Psychophysical and neurophysiological data suggest that illusory contours are processed in early visual cortical areas, and neuroimaging studies in humans have shown that Kanizsa-type illusory contours activate early retinotopic visual areas that are also activated by real contours. It is not known whether other types of illusory contours are processed by the same mechanisms, nor is it clear to what extent attentional effects may have influenced these results, as no attempt was made to match the salience of real and illusory stimuli in previous imaging studies. It therefore remains an open question whether there are any brain regions specifically involved in the perception of illusory contours. To address these questions, we have used 15O-butanol positron emission tomography (PET) and a novel kind of illusory contour stimulus that is induced only by aligned line ends. By employing a form discrimination task that was matched for attention and stimulus salience across conditions we were able to directly contrast perception of real and illusory contours. We found that the regions activated by illusory contour perception were the same as those activated by real contours. Only one region, located in the right fusiform gyrus, was significantly more strongly activated by perception of illusory contours than by real contours. In addition, a principal component analysis suggested that illusory contour perception is associated with a change in the correlation between V1 and V2. We conclude that different kinds of illusory contours are processed by the same cortical regions and that these regions overlap extensively with those involved in processing of real contours. At the regional level, perception of illusory contours thus appears to differ from perception of real contours by the degree of involvement of higher visual areas as well as by the nature of interaction between early visual areas. [ABSTRACT FROM AUTHOR]