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NeuroBlogs Daily Weekend

April 6, 2024

Open Access Brain Science, Lectures, & Podcasts

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SCIENCE

Latent network analysis of executive functions across development Executive
functions (EFs) are crucial for academic achievement, physical health, and
mental well-being. Previous studies using structural equation models revealed
EFs’ developmental organization, evolving from one factor in childhood to three
factors in adults: inhibition, cognitive flexibility, and updating. Recent
network model studies confirmed this differentiation from childhood to
adulthood. Reanalyzing previously published data from 1019 children (aged 7.8 to
15.3; 50.4% female; 59.1% White, 15.0% Latinx, 14.3% Bi-racial, 6.7% African
American, 4.2% Asian American, 0.6% Other), this study compared three analytical
methods to explore EF development: structural equation model, network model, and
the novel latent variable network model. All approaches supported fine-grained
EF-specific trajectories and differentiation throughout development, with
inhibition being central in childhood and updating in early adolescence.

Concurrent Encoding of Sequence Predictability and Event-Evoked Prediction Error
in Unfolding Auditory Patterns Human listeners possess an innate capacity to
discern patterns within rapidly unfolding sensory input. Core questions, guiding
ongoing research, focus on the mechanisms through which these representations
are acquired and whether the brain prioritizes or suppresses predictable sensory
signals. Previous work, using fast auditory sequences (tone-pips presented at a
rate of 20 Hz), revealed sustained response effects that appear to track the
dynamic predictability of the sequence. Here, we extend the investigation to
slower sequences (4 Hz), permitting the isolation of responses to individual
tones. Stimuli were 50 ms tone-pips, ordered into random (RND) and regular (REG;
a repeating pattern of 10 frequencies) sequences; Two timing profiles were
created: in “fast” sequences, tone-pips were presented in direct succession
(20 Hz); in “slow” sequences, tone-pips were separated by a 200 ms silent gap
(4 Hz). Naive participants (N = 22; both sexes) passively listened to these
sequences, while brain responses were recorded using magnetoencephalography
(MEG). Results unveiled a heightened magnitude of sustained brain responses in
REG when compared to RND patterns. This manifested from three tones after the
onset of the pattern repetition, even in the context of slower sequences
characterized by extended pattern durations (2,500 ms). This observation
underscores the remarkable implicit sensitivity of the auditory brain to
acoustic regularities. Importantly, brain responses evoked by single tones
exhibited the opposite pattern—stronger responses to tones in RND than REG
sequences. The demonstration of simultaneous but opposing sustained and evoked
response effects reveals concurrent processes that shape the representation of
unfolding auditory patterns.

Unraveling Temporal Dynamics of Multidimensional Statistical Learning in
Implicit and Explicit Systems: An X-Way Hypothesis Statistical learning enables
humans to involuntarily process and utilize different kinds of patterns from the
environment. However, the cognitive mechanisms underlying the simultaneous
acquisition of multiple regularities from different perceptual modalities remain
unclear. A novel multidimensional serial reaction time task was developed to
test 40 participants’ ability to learn simple first-order and complex
second-order relations between uni-modal visual and cross-modal audio-visual
stimuli. Using the difference in reaction times between sequenced and random
stimuli as the index of domain-general statistical learning, a significant
difference and dissociation of learning occurred between the initial and final
learning phases. Furthermore, we used a negative and positive
occurrence-frequency-and-reaction-time correlation to indicate implicit and
explicit learning, respectively, and found that learning simple uni-modal
patterns involved an implicit-to-explicit segue, while acquiring complex
cross-modal patterns required an explicit-to-implicit segue, resulting in a
X-shape crossing of regularity learning. Thus, we propose an X-way hypothesis to
elucidate the dynamic interplay between the implicit and explicit systems at two
distinct stages when acquiring various regularities in a multidimensional
probability space.

Theory of Coupled Neuronal-Synaptic Dynamics In neural circuits, synaptic
strengths influence neuronal activity by shaping network dynamics, and neuronal
activity influences synaptic strengths through activity-dependent plasticity.
Motivated by this fact, we study a recurrent-network model in which neuronal
units and synaptic couplings are interacting dynamic variables, with couplings
subject to Hebbian modification with decay around quenched random strengths.
Rather than assigning a specific role to the plasticity, we use dynamical
mean-field theory and other techniques to systematically characterize the
neuronal-synaptic dynamics, revealing a rich phase diagram. Adding Hebbian
plasticity slows activity in already chaotic networks and can induce chaos in
otherwise quiescent networks. Anti-Hebbian plasticity quickens activity and
produces an oscillatory component. Analysis of the Jacobian shows that Hebbian
and anti-Hebbian plasticity push locally unstable modes toward the real and
imaginary axes, respectively, explaining these behaviors. Both random-matrix and
Lyapunov analysis show that strong Hebbian plasticity segregates network
timescales into two bands, with a slow, synapse-dominated band driving the
dynamics, suggesting a flipped view of the network as synapses connected by
neurons. For increasing strength, Hebbian plasticity initially raises the
complexity of the dynamics, measured by the maximum Lyapunov exponent and
attractor dimension, but then decreases these metrics, likely due to the
proliferation of stable fixed points. We compute the marginally stable spectra
of such fixed points as well as their number, showing exponential growth with
network size. Finally, in chaotic states with strong Hebbian plasticity, a
stable fixed point of neuronal dynamics is destabilized by synaptic dynamics,
allowing any neuronal state to be stored as a stable fixed point by halting the
plasticity. This phase of freezable chaos offers a new mechanism for working
memory.

Sensory Drive Modifies Brain Dynamics and the Temporal Integration Window
Perception is suggested to occur in discrete temporal windows, clocked by cycles
of neural oscillations. An important testable prediction of this theory is that
individuals’ peak frequencies of oscillations should correlate with their
ability to segregate the appearance of two successive stimuli. An influential
study tested this prediction and showed that individual peak frequency of
spontaneously occurring alpha (8–12 Hz) correlated with the temporal segregation
threshold between two successive flashes of light [Samaha, J., & Postle, B. R.
The speed of alpha-band oscillations predicts the temporal resolution of visual
perception. Current Biology, 25, 2985–2990, 2015]. However, these findings were
recently challenged [Buergers, S., & Noppeney, U. The role of alpha oscillations
in temporal binding within and across the senses. Nature Human Behaviour, 6,
732–742, 2022]. To advance our understanding of the link between oscillations
and temporal segregation, we devised a novel experimental approach. Rather than
relying entirely on spontaneous brain dynamics, we presented a visual grating
before the flash stimuli that is known to induce continuous oscillations in the
gamma band (45–65 Hz). By manipulating the contrast of the grating, we found
that high contrast induces a stronger gamma response and a shorter temporal
segregation threshold, compared to low-contrast trials. In addition, we used a
novel tool to characterize sustained oscillations and found that, for half of
the participants, both the low- and high-contrast gratings were accompanied by a
sustained and phase-locked alpha oscillation. These participants tended to have
longer temporal segregation thresholds. Our results suggest that visual stimulus
drive, reflected by oscillations in specific bands, is related to the temporal
resolution of visual perception.

Postsynaptic receptors regulate presynaptic transmitter stability through
transsynaptic bridges Stable matching of neurotransmitters with their receptors
is fundamental to synapse function and reliable communication in neural
circuits. Presynaptic neurotransmitters regulate the stabilization of
postsynaptic transmitter receptors. Whether postsynaptic receptors regulate
stabilization of presynaptic transmitters has received less attention. Here, we
show that blockade of endogenous postsynaptic acetylcholine receptors (AChR) at
the neuromuscular junction destabilizes the cholinergic phenotype in motor
neurons and stabilizes an earlier, developmentally transient glutamatergic
phenotype. Further, expression of exogenous postsynaptic gamma-aminobutyric acid
type A receptors (GABAA receptors) in muscle cells stabilizes an earlier,
developmentally transient GABAergic motor neuron phenotype. Both AChR and
GABAA receptors are linked to presynaptic neurons through transsynaptic bridges.
Knockdown of specific components of these transsynaptic bridges prevents
stabilization of the cholinergic or GABAergic phenotypes. Bidirectional
communication can enforce a match between transmitter and receptor and ensure
the fidelity of synaptic transmission. Our findings suggest a potential role of
dysfunctional transmitter receptors in neurological disorders that involve the
loss of the presynaptic transmitter.

Enhanced mitochondrial fusion during a critical period of synaptic plasticity in
adult-born neurons Integration of new neurons into adult hippocampal circuits is
a process coordinated by local and long-range synaptic inputs. To achieve stable
integration and uniquely contribute to hippocampal function, immature neurons
are endowed with a critical period of heightened synaptic plasticity, yet it
remains unclear which mechanisms sustain this form of plasticity during neuronal
maturation. We found that as new neurons enter their critical period, a
transient surge in fusion dynamics stabilizes elongated mitochondrial
morphologies in dendrites to fuel synaptic plasticity. Conditional ablation of
fusion dynamics to prevent mitochondrial elongation selectively impaired spine
plasticity and synaptic potentiation, disrupting neuronal competition for stable
circuit integration, ultimately leading to decreased survival. Despite profuse
mitochondrial fragmentation, manipulation of competition dynamics was sufficient
to restore neuronal survival but left neurons poorly responsive to experience at
the circuit level. Thus, by enabling synaptic plasticity during the critical
period, mitochondrial fusion facilitates circuit remodeling by adult-born
neurons.

Centripetal integration of past events in hippocampal astrocytes regulated by
locus coeruleus An essential feature of neurons is their ability to centrally
integrate information from their dendrites. The activity of astrocytes, in
contrast, has been described as mostly uncoordinated across cellular
compartments without clear central integration. Here we report conditional
integration of calcium signals in astrocytic distal processes at their soma. In
the hippocampus of adult mice of both sexes, we found that global astrocytic
activity, as recorded with population calcium imaging, reflected past neuronal
and behavioral events on a timescale of seconds. Salient past events, indicated
by pupil dilations, facilitated the propagation of calcium signals from distal
processes to the soma. Centripetal propagation to the soma was reproduced by
optogenetic activation of the locus coeruleus, a key regulator of arousal, and
reduced by pharmacological inhibition of α1-adrenergic receptors. Together, our
results suggest that astrocytes are computational units of the brain that slowly
and conditionally integrate calcium signals upon behaviorally relevant events.



Language Neuroscience 29: Developmental language disorder and its neural basis with Dorothy Bishop

Big Biology 119: Biology as its own metaphor

The Brain Podcast: Do noradrenergic alterations in Parkinson’s disease indicate a therapeutic target? A combined PET & neuromelanin MRI study
Max BennetA Brief History of Intelligence: Evolution, AI, and the Five Breakthroughs That Made Our Brains

Nature & Nurture #138: Dr. Adriene Beltz - Hormones, Sex Differences, & Contraceptives

Converging Dialogues 328: Listening to Prozac: A Dialogue with Peter Kramer

NeuroBlogs Daily Weekend

Open Access Brain Science, Lectures, & Podcasts

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