Control of Visual Selection during Visual Search in the Human Brain

How do we find a target object in a cluttered visual scene? Targets carrying unique salient features can be found in parallel without directing attention, whereas targets defined by feature conjunctions or non-salient features need to be scrutinized in a serial attentional process in order to be identified. In this article, we review a series of experiments in which we used fMRI to probe the neural basis of this active search process in the human brain. In all experiments, we compared the fMRI signal between a difficult and an easy visual search (each performed without eye movements) in order to isolate neural activity reflecting the search process from other components such as stimulus responses and movement-related activity. The difficult search was either a conjunction search or a hard feature search and compared with an easy feature search, matched in visual stimulation and motor requirements. During both, the conjunction search and the hard feature search the frontal eye fields (FEF) and three parietal regions located in the intraparietal sulcus (IPS) were differentially activated: the anterior and posterior part of the intraparietal sulcus (AIPS, PIPS) as well as the junction of the intraparietal with the transverse occipital sulcus (IPTO). Only in PIPS, the modulation strength was most indistinguishable between conjunction and hard feature search. In a further experiment we showed that AIPS and IPTO are involved in visual conjunction search even in the absence of distractors; by contrast, the involvement of PIPS seems to depend on the presence of distractors. Taken together, these findings from these experiments demonstrate that all four key nodes of the human ’frontoparietal attention network’ are generally engaged in the covert selection process of visual search. But they also suggest that these areas play differential roles, perhaps reflecting different sub-processes in active search. We conclude by discussing a number of such sub-processes, such as the direction of spatial attention, visual feature binding, and the active suppression of distractors

Confidence predicts speed-accuracy tradeoff for subsequent decisions

When external feedback about decision outcomes is lacking, agents need to adapt their decision policies based on an internal estimate of the correctness of their choices (i.e., decision confidence). We hypothesized that agents use confidence to continuously update the tradeoff between the speed and accuracy of their decisions: When confidence is low in one decision, the agent needs more evidence before committing to a choice in the next decision, leading to slower but more accurate decisions. We tested this hypothesis by fitting a bounded accumulation decision model to behavioral data from three different perceptual choice tasks. Decision bounds indeed depended on the reported confidence on the previous trial, independent of objective accuracy. This increase in decision bound was predicted by a centro-parietal EEG component sensitive to confidence. We conclude that internally computed neural signals of confidence predict the ongoing adjustment of decision policies.</jats:p

Observing the Formation of Long-range Order during Bose-Einstein Condensation

We have experimentally investigated the formation of off-diagonal long-range order in a gas of ultracold atoms. A magnetically trapped atomic cloud prepared in a highly nonequilibrium state thermalizes and thereby crosses the Bose-Einstein condensation phase transition. The evolution of phase coherence between different regions of the sample is constantly monitored and information on the spatial first-order correlation function is obtained. We observe the growth of the spatial coherence and the formation of long-range order in real time and compare it to the growth of the atomic density. Moreover, we study the evolution of the momentum distribution during the nonequilibrium formation of the condensate.Comment: 4 pages, 4 figure

Choices change the temporal weighting of decision evidence

Many decisions result from the accumulation of decision-relevant information (evidence) over time. Even when maximizing decision accuracy requires weighting all the evidence equally, decision-makers often give stronger weight to evidence occurring early or late in the evidence stream. Here, we show changes in such temporal biases within participants as a function of intermittent judgments about parts of the evidence stream. Human participants performed a decision task that required a continuous estimation of the mean evidence at the end of the stream. The evidence was either perceptual (noisy random dot motion) or symbolic (variable sequences of numbers). Participants also reported a categorical judgment of the preceding evidence half-way through the stream in one condition or executed an evidence-independent motor response in another condition. The relative impact of early versus late evidence on the final estimation flipped between these two conditions. In particular, participants’ sensitivity to late evidence after the intermittent judgment, but not the simple motor response, was decreased. Both the intermittent response as well as the final estimation reports were accompanied by nonluminance-mediated increases of pupil diameter. These pupil dilations were bigger during intermittent judgments than simple motor responses and bigger during estimation when the late evidence was consistent than inconsistent with the initial judgment. In sum, decisions activate pupil-linked arousal systems and alter the temporal weighting of decision evidence. Our results are consistent with the idea that categorical choices in the face of uncertainty induce a change in the state of the neural circuits underlying decision-making. NEW & NOTEWORTHY The psychology and neuroscience of decision-making have extensively studied the accumulation of decision-relevant information toward a categorical choice. Much fewer studies have assessed the impact of a choice on the processing of subsequent information. Here, we show that intermittent choices during a protracted stream of input reduce the sensitivity to subsequent decision information and transiently boost arousal. Choices might trigger a state change in the neural machinery for decision-making

Coupling of pupil- and neuronal population dynamics reveals diverse influences of arousal on cortical processing

Fluctuations in arousal, controlled by subcortical neuromodulatory systems, continuously shape cortical state, with profound consequences for information processing. Yet, how arousal signals influence cortical population activity in detail has so far only been characterized for a few selected brain regions. Traditional accounts conceptualize arousal as a homogeneous modulator of neural population activity across the cerebral cortex. Recent insights, however, point to a higher specificity of arousal effects on different components of neural activity and across cortical regions. Here, we provide a comprehensive account of the relationships between fluctuations in arousal and neuronal population activity across the human brain. Exploiting the established link between pupil size and central arousal systems, we performed concurrent magnetoencephalographic (MEG) and pupillographic recordings in a large number of participants, pooled across three laboratories. We found a cascade of effects relative to the peak timing of spontaneous pupil dilations: Decreases in low-frequency (2-8 Hz) activity in temporal and lateral frontal cortex, followed by increased high-frequency (>64 Hz) activity in mid-frontal regions, followed by monotonic and inverted U relationships with intermediate frequency-range activity (8-32 Hz) in occipito-parietal regions. Pupil-linked arousal also coincided with widespread changes in the structure of the aperiodic component of cortical population activity, indicative of changes in the excitation-inhibition balance in underlying microcircuits. Our results provide a novel basis for studying the arousal modulation of cognitive computations in cortical circuits

Cavity QED with a Bose-Einstein condensate

Cavity quantum electrodynamics (cavity QED) describes the coherent interaction between matter and an electromagnetic field confined within a resonator structure, and is providing a useful platform for developing concepts in quantum information processing. By using high-quality resonators, a strong coupling regime can be reached experimentally in which atoms coherently exchange a photon with a single light-field mode many times before dissipation sets in. This has led to fundamental studies with both microwave and optical resonators. To meet the challenges posed by quantum state engineering and quantum information processing, recent experiments have focused on laser cooling and trapping of atoms inside an optical cavity. However, the tremendous degree of control over atomic gases achieved with Bose-Einstein condensation has so far not been used for cavity QED. Here we achieve the strong coupling of a Bose-Einstein condensate to the quantized field of an ultrahigh-finesse optical cavity and present a measurement of its eigenenergy spectrum. This is a conceptually new regime of cavity QED, in which all atoms occupy a single mode of a matter-wave field and couple identically to the light field, sharing a single excitation. This opens possibilities ranging from quantum communication to a wealth of new phenomena that can be expected in the many-body physics of quantum gases with cavity-mediated interactions.Comment: 6 pages, 4 figures; version accepted for publication in Nature; updated Fig. 4; changed atom numbers due to new calibratio

Action planning and the timescale of evidence accumulation

Perceptual decisions are based on the temporal integration of sensory evidence for different states of the outside world. The timescale of this integration process varies widely across behavioral contexts and individuals, and it is diagnostic for the underlying neural mechanisms. In many situations, the decision-maker knows the required mapping between perceptual evidence and motor response (henceforth termed “sensory-motor contingency”) before decision formation. Here, the integrated evidence can be directly translated into a motor plan and, indeed, neural signatures of the integration process are evident as build-up activity in premotor brain regions. In other situations, however, the sensory-motor contingencies are unknown at the time of decision formation. We used behavioral psychophysics and computational modeling to test if knowledge about sensory-motor contingencies affects the timescale of perceptual evidence integration. We asked human observers to perform the same motion discrimination task, with or without trial-to-trial variations of the mapping between perceptual choice and motor response. When the mapping varied, it was either instructed before or after the stimulus presentation. We quantified the timescale of evidence integration under these different sensory-motor mapping conditions by means of two approaches. First, we analyzed subjects’ discrimination threshold as a function of stimulus duration. Second, we fitted a dynamical decision-making model to subjects’ choice behavior. The results from both approaches indicated that observers (i) integrated motion information for several hundred ms, (ii) used a shorter than optimal integration timescale, and (iii) used the same integration timescale under all sensory-motor mappings. We conclude that the mechanisms limiting the timescale of perceptual decisions are largely independent from long-term learning (under fixed mapping) or rapid acquisition (under variable mapping) of sensory-motor contingencies. This conclusion has implications for neurophysiological and neuroimaging studies of perceptual decision-making

Catecholaminergic neuromodulation shapes intrinsic MRI functional connectivity in the human brain

The brain commonly exhibits spontaneous (i.e., in the absence of a task) fluctuations in neural activity that are correlated across brain regions. It has been established that the spatial structure, or topography, of these intrinsic correlations is in part determined by the fixed anatomical connectivity between regions. However, it remains unclear which factors dynamically sculpt this topography as a function of brain state. Potential candidate factors are subcortical catecholaminergic neuromodulatory systems, such as the locus ceruleus-norepinephrine system, which send diffuse projections to most parts of the forebrain. Here, we systematically characterized the effects of endogenous central neuromodulation on correlated fluctuations during rest in the human brain. Using a double-blind placebo-controlled crossover design, we pharmacologically increased synaptic catecholamine levels by administering atomoxetine, an NE transporter blocker, and examined the effects on the strength and spatial structure of resting-state MRI functional connectivity. First, atomoxetine reduced the strength of inter-regional correlations across three levels of spatial organization, indicating that catecholamines reduce the strength of functional interactions during rest. Second, this modulatory effect on intrinsic correlations exhibited a substantial degree of spatial specificity: the decrease in functional connectivity showed an anterior-posterior gradient in the cortex, depended on the strength of baseline functional connectivity, and was strongest for connections between regions belonging to distinct resting-state networks. Thus, catecholamines reduce intrinsic correlations in a spatially heterogeneous fashion. We conclude that neuromodulation is an important factor shaping the topography of intrinsic functional connectivity

Evidence of Weak Habitat Specialisation in Microscopic Animals

Macroecology and biogeography of microscopic organisms (any living organism smaller than 2 mm) are quickly developing into fruitful research areas. Microscopic organisms also offer the potential for testing predictions and models derived from observations on larger organisms due to the feasibility of performing lab and mesocosm experiments. However, more empirical knowledge on the similarities and differences between micro- and macro-organisms is needed to ascertain how much of the results obtained from the former can be generalised to the latter. One potential misconception, based mostly on anedoctal evidence rather than explicit tests, is that microscopic organisms may have wider ecological tolerance and a lower degree of habitat specialisation than large organisms. Here we explicitly test this hypothesis within the framework of metacommunity theory, by studying host specificify in the assemblages of bdelloid rotifers (animals about 350 µm in body length) living in different species of lichens in Sweden. Using several regression-based and ANOVA analyses and controlling for both spatial structure and the kind of substrate the lichen grow over (bark vs rock), we found evidence of significant but weak species-specific associations between bdelloids and lichens, a wide overlap in species composition between lichens, and wide ecological tolerance for most bdelloid species. This confirms that microscopic organisms such as bdelloids have a lower degree of habitat specialisation than larger organisms, although this happens in a complex scenario of ecological processes, where source-sink dynamics and geographic distances seem to have no effect on species composition at the analysed scale