An fMRI study of parietal cortex involvement in the visual guidance of locomotion

Locomoting through the environment typically involves anticipating impending changes in heading trajectory in addition to maintaining the current direction of travel. We explored the neural systems involved in the “far road” and “near road” mechanisms proposed by Land and Horwood (1995) using simulated forward or backward travel where participants were required to gauge their current direction of travel (rather than directly control it). During forward egomotion, the distant road edges provided future path information, which participants used to improve their heading judgments. During backward egomotion, the road edges did not enhance performance because they no longer provided prospective information. This behavioral dissociation was reflected at the neural level, where only simulated forward travel increased activation in a region of the superior parietal lobe and the medial intraparietal sulcus. Providing only near road information during a forward heading judgment task resulted in activation in the motion complex. We propose a complementary role for the posterior parietal cortex and motion complex in detecting future path information and maintaining current lane positioning, respectively. (PsycINFO Database Record (c) 2010 APA, all rights reserved)

Increased serum androstenedione in adults with autism spectrum conditions

Molecular and behavioural evidence points to an association between sex-steroid hormones and autism spectrum conditions (ASC) and/or autistic traits. Prenatal androgen levels are associated with autistic traits, and several genes involved in steroidogenesis are associated with autism, Asperger Syndrome and/or autistic traits. Furthermore, higher rates of androgen-related conditions (such as Polycystic Ovary Syndrome, hirsutism, acne and hormone-related cancers) are reported in women with autism spectrum conditions. A key question therefore is if serum levels of gonadal and adrenal sex-steroids (particularly testosterone, estradiol, dehydroepiandrosterone sulfate and androstenedione) are elevated in individuals with ASC. This was tested in a total sample of n=166 participants. The final eligible sample for hormone analysis comprised n=128 participants, n=58 of whom had a diagnosis of Asperger Syndrome or high functioning autism (33 males and 25 females) and n=70 of whom were age- and IQ-matched typical controls (39 males and 31 females). ASC diagnosis (without any interaction with sex) strongly predicted androstenedione levels (p<0.01), and serum androstenedione levels were significantly elevated in the ASC group (Mann-Whitney W=2677, p=0.002), a result confirmed by permutation testing in females (permutation-corrected p=0.02). This result is discussed in terms of androstenedione being the immediate precursor of, and being converted into, testosterone, dihydrotestosterone, or estrogens in hormone-sensitive tissues and organs.

Effects of glucose, propionate and splanchnic hormones on neuropeptide mRNA concentrations in the ovine hypothalamus

The capacity for glucose, propionate or hormones of splanchnic origin to influence appetite by directly regulating the expression of neuropeptides in the feeding centres of the hypothalamus of the ruminant is not described. Therefore, our objective was to measure the direct effect of metabolites (glucose and propionate) or hormones [insulin, cholecystokinin (CCK), glucagon-like peptide-1 (GLP-1) and polypeptide YY (PYY)] on hypothalamic mRNA concentrations for neuropeptide Y (NPY), agouti-related peptide (AgRP) and proopiomelanocortin (POMC) following in vitro incubation. Hypothalamic tissue from 4- to 5-month-old lambs was obtained at slaughter and immediately incubated in culture media for 2 h at 36 °C. Treatments included a control Dulbecco’s modified Eagle medium (DMEM) containing 1 mm glucose or DMEM with the following additions: 10 mm glucose, 1 mm propionate, 1 nm insulin, 120 pm GLP-1, 100 pm PYY, 80 pm CCK or 10 mm glucose plus 1 nm insulin. The abundance of mRNA for NPY, AgRP and POMC was measured using quantitative reverse transcriptase PCR. Fisher’s protected LSD test was used to compare changes in relative mRNA concentrations for the hypothalamus incubated in the control media vs. the rest of the treatments. The media containing glucose plus insulin increased POMC mRNA concentration (p < 0.05), but did not affect NPY or AgRP mRNA concentration. There were no effects observed for the other treatments (p > 0.20). Results of the present study are consistent with the concept that effects of propionate on feed intake in ruminants is not mediated through direct effects on the hypothalamus, and that insulin is required for an effect of glucose on hypothalamic POMC expression.

The primary somatosensory cortex largely contributes to the early part of the cortical response elicited by nociceptive stimuli.

Research on the cortical sources of nociceptive laser-evoked brain potentials (LEPs) began almost two decades ago (Tarkka and Treede, 1993). Whereas there is a large consensus on the sources of the late part of the LEP waveform (N2 and P2 waves), the relative contribution of the primary somatosensory cortex (S1) to the early part of the LEP waveform (N1 wave) is still debated. To address this issue we recorded LEPs elicited by the stimulation of four limbs in a large population (n=35). Early LEP generators were estimated both at single-subject and group level, using three different approaches: distributed source analysis, dipolar source modeling, and probabilistic independent component analysis (ICA). We show that the scalp distribution of the earliest LEP response to hand stimulation was maximal over the central-parietal electrodes contralateral to the stimulated side, while that of the earliest LEP response to foot stimulation was maximal over the central-parietal midline electrodes. Crucially, all three approaches indicated hand and foot S1 areas as generators of the earliest LEP response. Altogether, these findings indicate that the earliest part of the scalp response elicited by a selective nociceptive stimulus is largely explained by activity in the contralateral S1, with negligible contribution from the secondary somatosensory cortex (S2).

EEG activation differences in the pre-motor cortex and supplementary motor area between normal individuals with high and low traits of autism

The human mirror neuron system (hMNS) is believed to provide a basic mechanism for social cognition. Event-related desynchronization (ERD) in alpha (8–12 Hz) and low beta band (12–20 Hz) over sensori-motor cortex has been suggested to index mirror neurons' activity. We tested whether autistic traits revealed by high and low scores on the Autistic Quotient (AQ) in the normal population are linked to variations in the electroencephalogram (EEG) over motor, pre-motor cortex and supplementary motor area (SMA) during action observation. Results revealed that in the low AQ group, the pre-motor cortex and SMA were more active during hand action than static hand observation whereas in the high AQ group the same areas were active both during static and hand action observation. In fact participants with high traits of autism showed greater low beta ERD while observing the static hand than those with low traits and this low beta ERD was not significantly different when they watched hand actions. Over primary motor cortex, the classical alpha and low beta ERD during hand actions relative to static hand observation was found across all participants. These findings suggest that the observation–execution matching system works differently according to the degree of autism traits in the normal population and that this is differentiated in terms of the EEG according to scalp site and bandwidth.

Associating spontaneous with evoked activity in a neural mass model of cat visual cortex

Spontaneous activity of the brain at rest frequently has been considered a mere backdrop to the salient activity evoked by external stimuli or tasks. However, the resting state of the brain consumes most of its energy budget, which suggests a far more important role. An intriguing hint comes from experimental observations of spontaneous activity patterns, which closely resemble those evoked by visual stimulation with oriented gratings, except that cortex appeared to cycle between different orientation maps. Moreover, patterns similar to those evoked by the behaviorally most relevant horizontal and vertical orientations occurred more often than those corresponding to oblique angles. We hypothesize that this kind of spontaneous activity develops at least to some degree autonomously, providing a dynamical reservoir of cortical states, which are then associated with visual stimuli through learning. To test this hypothesis, we use a biologically inspired neural mass model to simulate a patch of cat visual cortex. Spontaneous transitions between orientation states were induced by modest modifications of the neural connectivity, establishing a stable heteroclinic channel. Significantly, the experimentally observed greater frequency of states representing the behaviorally important horizontal and vertical orientations emerged spontaneously from these simulations. We then applied bar-shaped inputs to the model cortex and used Hebbian learning rules to modify the corresponding synaptic strengths. After unsupervised learning, different bar inputs reliably and exclusively evoked their associated orientation state; whereas in the absence of input, the model cortex resumed its spontaneous cycling. We conclude that the experimentally observed similarities between spontaneous and evoked activity in visual cortex can be explained as the outcome of a learning process that associates external stimuli with a preexisting reservoir of autonomous neural activity states. Our findings hence demonstrate how cortical connectivity can link the maintenance of spontaneous activity in the brain mechanistically to its core cognitive functions.

Increases in prefrontal cortex activity when regulating negative emotion predicts symptom severity trajectory over six months in depression

Context: Emotion regulation is critically disrupted in depression and use of paradigms tapping these processes may uncover essential changes in neurobiology during treatment. In addition, as neuroimaging outcome studies of depression commonly utilize solely baseline and endpoint data – which is more prone to week-to week noise in symptomatology – we sought to use all data points over the course of a six month trial. Objective: To examine changes in neurobiology resulting from successful treatment. Design: Double-blind trial examining changes in the neural circuits involved in emotion regulation resulting from one of two antidepressant treatments over a six month trial. Participants were scanned pretreatment, at 2 months and 6 months posttreatment. Setting: University functional magnetic resonance imaging facility. Participants: 21 patients with Major Depressive Disorder and without other Axis I or Axis II diagnoses and 14 healthy controls. Interventions: Venlafaxine XR (doses up to 300mg) or Fluoxetine (doses up to 80mg). Main Outcome Measure: Neural activity, as measured using functional magnetic resonance imaging during performance of an emotion regulation paradigm as well as regular assessments of symptom severity by the Hamilton Rating Scale for Depression. To utilize all data points, slope trajectories were calculated for rate of change in depression severity as well as rate of change of neural engagement. Results: Those depressed individuals showing the steepest decrease in depression severity over the six months were those individuals showing the most rapid increases in BA10 and right DLPFC activity when regulating negative affect over the same time frame. This relationship was more robust than when using solely the baseline and endpoint data. Conclusions: Changes in PFC engagement when regulating negative affect correlate with changes in depression severity over six months. These results are buttressed by calculating these statistics which are more reliable and robust to week-to-week variation than difference scores.

Metabifurcation analysis of a mean field model of the cortex

Mean field models (MFMs) of cortical tissue incorporate salient, average features of neural masses in order to model activity at the population level, thereby linking microscopic physiology to macroscopic observations, e.g., with the electroencephalogram (EEG). One of the common aspects of MFM descriptions is the presence of a high-dimensional parameter space capturing neurobiological attributes deemed relevant to the brain dynamics of interest. We study the physiological parameter space of a MFM of electrocortical activity and discover robust correlations between physiological attributes of the model cortex and its dynamical features. These correlations are revealed by the study of bifurcation plots, which show that the model responses to changes in inhibition belong to two archetypal categories or “families”. After investigating and characterizing them in depth, we discuss their essential differences in terms of four important aspects: power responses with respect to the modeled action of anesthetics, reaction to exogenous stimuli such as thalamic input, and distributions of model parameters and oscillatory repertoires when inhibition is enhanced. Furthermore, while the complexity of sustained periodic orbits differs significantly between families, we are able to show how metamorphoses between the families can be brought about by exogenous stimuli. We here unveil links between measurable physiological attributes of the brain and dynamical patterns that are not accessible by linear methods. They instead emerge when the nonlinear structure of parameter space is partitioned according to bifurcation responses. We call this general method “metabifurcation analysis”. The partitioning cannot be achieved by the investigation of only a small number of parameter sets and is instead the result of an automated bifurcation analysis of a representative sample of 73,454 physiologically admissible parameter sets. Our approach generalizes straightforwardly and is well suited to probing the dynamics of other models with large and complex parameter spaces.

Classification of cortical microcircuits based on micro-electrode-array data from slices of rat barrel cortex

The bewildering complexity of cortical microcircuits at the single cell level gives rise to surprisingly robust emergent activity patterns at the level of laminar and columnar local field potentials (LFPs) in response to targeted local stimuli. Here we report the results of our multivariate data-analytic approach based on simultaneous multi-site recordings using micro-electrode-array chips for investigation of the microcircuitary of rat somatosensory (barrel) cortex. We find high repeatability of stimulus-induced responses, and typical spatial distributions of LFP responses to stimuli in supragranular, granular, and infragranular layers, where the last form a particularly distinct class. Population spikes appear to travel with about 33 cm/s from granular to infragranular layers. Responses within barrel related columns have different profiles than those in neighbouring columns to the left or interchangeably to the right. Variations between slices occur, but can be minimized by strictly obeying controlled experimental protocols. Cluster analysis on normalized recordings indicates specific spatial distributions of time series reflecting the location of sources and sinks independent of the stimulus layer. Although the precise correspondences between single cell activity and LFPs are still far from clear, a sophisticated neuroinformatics approach in combination with multi-site LFP recordings in the standardized slice preparation is suitable for comparing normal conditions to genetically or pharmacologically altered situations based on real cortical microcircuitry.

Sustained striatal activity predicts eudaimonic well-being and cortisol output

Eudaimonic well-being—a sense of purpose, meaning, and engagement with life—is protective against psychopathology and predicts physical health, including lower levels of the stress hormone cortisol. Although it has been suggested that the ability to engage the neural circuitry of reward may promote well-being and mediate the relationship between well-being and health, this hypothesis has remained untested. To test this hypothesis, we had participants view positive, neutral, and negative images while fMRI data were collected. Individuals with sustained activity in the striatum and dorsolateral prefrontal cortex to positive stimuli over the course of the scan session reported greater well-being and had lower cortisol output. This suggests that sustained engagement of reward circuitry in response to positive events underlies well-being and adaptive regulation of the hypothalamic-pituitary-adrenal axis.

SSRI administration reduces resting state functional connectivity in dorso-medial prefrontal cortex

Recent evidence suggests that an area in the dorsal medial prefrontal cortex (dorsal nexus) shows dramatic increases in connectivity across a network of brain regions in depressed patients during the resting state;1 this increase in connectivity is suggested to represent hotwiring of areas involved in disparate cognitive and emotional functions.1, 2, 3 Sheline et al.1 concluded that antidepressant action may involve normalisation of the elevated resting state functional connectivity seen in depressed patients. However, the effects of conventional pharmacotherapy for depression on this resting state functional connectivity is not known and the effects of antidepressant treatment in depressed patients may be confounded by change in symptoms following treatment.

Direct evidence for attention-dependent influences of the frontal eye-fields on feature-responsive visual cortex

Voluntary selective attention can prioritize different features in a visual scene. The frontal eye-fields (FEF) are one potential source of such feature-specific top-down signals, but causal evidence for influences on visual cortex (as was shown for "spatial" attention) has remained elusive. Here, we show that transcranial magnetic stimulation (TMS) applied to right FEF increased the blood oxygen level-dependent (BOLD) signals in visual areas processing "target feature" but not in "distracter feature"-processing regions. TMS-induced BOLD signals increase in motion-responsive visual cortex (MT+) when motion was attended in a display with moving dots superimposed on face stimuli, but in face-responsive fusiform area (FFA) when faces were attended to. These TMS effects on BOLD signal in both regions were negatively related to performance (on the motion task), supporting the behavioral relevance of this pathway. Our findings provide new causal evidence for the human FEF in the control of nonspatial "feature"-based attention, mediated by dynamic influences on feature-specific visual cortex that vary with the currently attended property.