Temporal unpredictability of a stimulus sequence affects brain activation differently depending on cognitive task demands

Koppe, Georgia; Gruppe, Harald; Sammer, Gebhard; Gallhofer, Bernd; Kirsch, Peter; Lis, Stefanie

doi:10.1016/j.neuroimage.2014.07.008

Cited by 17 publications

(27 citation statements)

References 69 publications

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“…attractor states, suffices to explain WM functions 9, 10 . Here, we considered the N -back task with variances in the timing of input stimuli 22 to draw conclusions on this dynamics. First, we showed that in purely transient systems the information about the N past stimuli is stored, as expected, in distinguishable trajectories.…”

Section: Discussionmentioning

confidence: 99%

“…Dependent on the timing of the stimuli, this information has to be continuously updated. Interestingly, whether the stimuli are presented with exact inter-stimulus timing or with unreliable timing does not influence the subject’s performance of solving the N -back task 22 . This result indicates that the mechanisms implementing WM are robust against variance in the timing of the input stimuli.…”

Section: Introductionmentioning

confidence: 98%

“…For instance, listening to spoken language requires the ability to deal with different and irregular speech rates. The influence of such variance in the stimuli timing on the WM operation has been mainly analyzed on the psychological level 22 using, amongst others, the so-called N -back task. In this task a subject is exposed to a stream of different stimuli 23, 24 .…”

Section: Introductionmentioning

confidence: 99%

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Working Memory Requires a Combination of Transient and Attractor-Dominated Dynamics to Process Unreliably Timed Inputs

Nachstedt

Tetzlaff

2017

Sci Rep

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Working memory stores and processes information received as a stream of continuously incoming stimuli. This requires accurate sequencing and it remains puzzling how this can be reliably achieved by the neuronal system as our perceptual inputs show a high degree of temporal variability. One hypothesis is that accurate timing is achieved by purely transient neuronal dynamics; by contrast a second hypothesis states that the underlying network dynamics are dominated by attractor states. In this study, we resolve this contradiction by theoretically investigating the performance of the system using stimuli with differently accurate timing. Interestingly, only the combination of attractor and transient dynamics enables the network to perform with a low error rate. Further analysis reveals that the transient dynamics of the system are used to process information, while the attractor states store it. The interaction between both types of dynamics yields experimentally testable predictions and we show that this way the system can reliably interact with a timing-unreliable Hebbian-network representing long-term memory. Thus, this study provides a potential solution to the long-standing problem of the basic neuronal dynamics underlying working memory.Humans and animals continuously receive information conveyed by stimuli from the environment. To survive, the brain has to store and process this stream of information which is mainly attributed to the processes of working memory (WM 1, 2 ). These two distinct abilities of WM, to store and to process information, yield a debate about the underlying neuronal network dynamics 3-5 : the network dynamics might either follow (i) attractor or (ii) transient dynamics.Attractor dynamics denotes neuronal network dynamics which is dominated by groups of neurons being persistently active. In general, such a persistent activation is related to an attractor state of the dynamics, with each attractor associated to a specific information content 3, 6-8 . Several experimental and theoretical studies hypothesize that the dynamics underlying WM are dominated by such persistent dynamics 5,[8][9][10] . In contrast to attractor dynamics, neuronal networks with transient dynamics are dominated by an attractor-less continuous flow of neuronal activity across a possibly large neuronal population [11][12][13][14] . This type of dynamics implies a high diversity and complexity which is linked by theoretical studies with a large computational capacity required to process information [15][16][17] . These theoretical studies as well as several pieces of experimental evidence 18-20 yield the hypothesis that the dynamics underlying WM are dominated by transient dynamics 20,21 . Thus, although the two hypotheses -attractor or transient dynamics -seem to contradict each other, experimental and theoretical evidence supports both yielding a debate about the neuronal network dynamics underlying WM 5 .To resolve this contradiction, in this study, we consider the fact that the timing of stimuli received by the WM i...

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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Working Memory Requires a Combination of Transient and Attractor-Dominated Dynamics to Process Unreliably Timed Inputs

Nachstedt

Tetzlaff

2017

Sci Rep

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“…Beyond attention, the parietal areas found here have been considered significant in representing prediction-related activity. During temporally unpredictable situations, right parietal activations have been observed, independent of WM load [26], and posterior parietal cortex has been associated with generating temporal expectancies [27]. In a recent meta-analysis, bilateral inferior parietal lobule (focus in IPS) was found to be sensitive to the magnitude of surprise in a reinforcement learning situation [28].…”

Section: Discussionmentioning

confidence: 99%

Glutamatergic modulation of auditory cortex connectivity with attentional brain networks in unpredictable perceptual environment

Kompus

Volehaugen

Craven

et al. 2019

Preprint

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In a stable environment the brain can minimize processing required for sensory input by forming a predictive model of the surrounding world and suppressing neural response to predicted stimuli.Unpredicted stimuli lead to a prediction error signal propagation through the perceptual network, and resulting adjustment to the predictive model. The inter-regional plasticity which enables the model-building and model-adjustment is hypothesized to be mediated via glutamatergic receptors.While pharmacological challenge studies with glutamate receptor ligands have demonstrated impact on prediction-error indices, it is not clear how inter-individual differences in the glutamate system affect the prediction-error processing in non-medicated state. In the present study we examined 20 healthy young subjects with resting-state proton MRS spectroscopy to characterize glutamate+glutamine (rs-Glx) levels in their Heschl's gyrus (HG), and related this to HG functional connectivity during a roving auditory oddball protocol. No rs-Glx effects were found within the frontotemporal prediction-error network. Larger rs-Glx signal was related to stronger connectivity between HG and bilateral inferior parietal lobule during unpredictable auditory stimulation. We also found effects of rs-Glx on the coherence of default mode network (DMN) and frontoparietal network (FPN) during unpredictable auditory stimulation. Our results demonstrate the importance of Glx in modulating long-range connections and wider networks in the brain during perceptual inference.

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“…Foram analisados 10 comportamentos agrupados da seguinte forma: Categoria de comportamentos dirigidos ao bebedouro 3 Mais do que saber a resposta correta a partir da distribuição dos estímulos apresentados no ambiente, é preciso saber quando as ações devem ser executadas, para uma melhor eficiência na estratégia comportamental. O NAC aparece como uma estrutura que organiza temporalmente as ações do animal no sentido de avaliar a chegada de estímulos iminentes (Singh et al, 2011;Koppe et al, 2014). Esta relação entre NAC e controle temporal ainda apresenta dados divergentes.…”

Section: Repertório Comportamental E Omissãounclassified

Efeitos da omissão do reforço sobre o repertório comportamental em ratos com lesão do núcleo accumbens

Bernardes¹

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Temporal unpredictability of a stimulus sequence affects brain activation differently depending on cognitive task demands

Cited by 17 publications

References 69 publications

Working Memory Requires a Combination of Transient and Attractor-Dominated Dynamics to Process Unreliably Timed Inputs

Working Memory Requires a Combination of Transient and Attractor-Dominated Dynamics to Process Unreliably Timed Inputs

Glutamatergic modulation of auditory cortex connectivity with attentional brain networks in unpredictable perceptual environment

Efeitos da omissão do reforço sobre o repertório comportamental em ratos com lesão do núcleo accumbens

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