When you memorize something, the
brain creates a nerve-impulse code to create a representation of the
information represented in brain, and this code can get stored in memory. Upon
retrieval, the code is replayed, and thus what the code represents becomes
consciously available again as a simulation. At least that’s the theory. Until
now, the evidence for this explanation has been derived mostly from rodents.
But now rather direct evidence is available from humans.
In one new study, human subjects
created memory associations between word pairs, while experimenters
simultaneously recorded single-neuron impulses and their associated field
potentials from an implanted microelectrode array in the medial temporal cortex,
which is known to participate in memory formation. The EEG was also recorded from
subdural electrodes implanted over the temporal cortex immediately above the
microelectrode array. This allowed simultaneous observation of the local nerve
impulse discharges, their associated local field potentials, and the EEG during
memory formation and retrieval after a brief distraction period.
Recordings revealed the
well-known relationship that EEG signals often have superimposed low-voltage
high-frequency waves, which are called ripples. As expected, the ripples
appeared at the same time of the impulse discharges from the microelectrodes,
indicating that the impulses actually cause the small field potential changes
of ripples.
In the top signal, we have the sum of a fast and slow
oscillations, where the power of fast oscillation's envelope changes with the
phase of the slower oscillation. The bottom signal shows only the filtered fast
oscillation and the variation in its power. As it is obvious from comparison of
two signals, the fast rhythm's power is always maximum at a certain coupled
phase of slower oscillation (From Samiee et al.).
In the experiment, impulse burst
clusters occurred throughout the presentation of word pairs while subjects were
encoding the pairs. Trial-specific spike sequences observed during encoding
were replayed during correct recall. As expected, ripples during recall
appeared at the same time as the impulse sequences.
Not mentioned by the authors is
that their findings have implications for neural correlates of consciousness.
After all, forming the word-pair associations was a conscious operation. In the
field of consciousness research, neural correlates are clearly evident in the
EEG in that the frequency of voltage shifts predictably as the brain progresses
from large slow waves during anesthesia or sleep to increasingly faster and
smaller waves during alert arousal.
Relatively high frequencies (40-200 waves per second) appear more
prominently when the brain is working on difficult tasks. Moreover, hard tasks
are associated with more phase-locking of the EEG oscillations at different
locations of the cortex.
Conscious perceptions seem to involve
short- and long-range oscillations in the vertically oriented network columns
in the cortex. Each column contains a local network that processes input
locally in oscillatory activity that is gated at certain frequencies by inhibitory
neurons in the circuit.
At the same time, local
oscillations from large pyramidal cell firings spread to distant columns both
within and between the cortical hemispheres. The frequencies of this long-range
activity may be slower because of the longer impulse conduction and synaptic
delays. Collectively, local and distant networks interact and may likely be the
basis for consciousness. The electrographic correlate is that of fast
frequencies from local processing being nested within more globally generated
slow frequencies. The timing phase relationships would clearly influence how
much integration of local and distant processing occurs and the likelihood that
the processing could be consciously perceived.
Many experiments have shown that
selective attention is needed for conscious perception. Such attention
activates local processing (and ripples in the local field potential). Bear in
mind, however, that the ripples are not the source of processing but rather an
associated manifestation of the processing that is actually occurring via the
impulse timing in the local circuitry.
Two basic kinds of coupling can
be seen in brainwave activity: 1) the phase of the slower frequency modulates
the faster frequency, and (2) the phase coupling between two overlapping
frequencies occurs when one frequency is a harmonic multiple of the other.
Conscious processing seems to be
crucially dependent on the cross-frequency coherence of neural activity that
can be seen at the local circuit level in multiple local sites of neocortex, hippocampus, and basal ganglia.
There are different varieties of cross-frequency coupling (phase-phase,
amplitude-amplitude, and phase-amplitude coupling), each of which may reflect
distinctive processing. Such coherence differs across brain areas
in a task-relevant manner, and changes quickly in response to sensory, motor,
and cognitive events, and correlates with performance in learning tasks. Moreover,
cross-frequency coherence increases with level of task demand. For
example, continuous EEG recordings obtained during an arithmetic task, rest and
breath focus revealed that cross-frequency alpha and theta peak-frequency
coherence significantly higher when cognitive demands increased
(Rodriguez-Larios and Alaerts, (2019). What is likely to remain enigmatic is
how such cross-frequency coupling yields a conscious perception.
The most significant neural
correlation of consciousness may prove to be time locking of nested oscillation
of different frequencies whose underlying impulse patterns carry different
aspects of information. The time locking of nested high- and low-frequency
activity likely increases information throughput in the local circuits
participating in selective attention, occludes noisy disruption from other
inputs, and improves the signal-to-noise ratio of neural activity that is
processing the target of attention. Parsimonious as this view might be, it
still does not fully explain how a conscious percept emerges.
Sources:
Rodriguez_Larios, Julio and Alaerts, Kaat (2019). Tracking
transient changes in the neural frequency architecture: harmonic relations
between theta and alpha peaks facilitate cognitive performance. J. Neurosci. 7
August, 39 (32) 6291-6298; DOI: https://doi.org/10.1523/JNEUROSCI.2919-18.2019
Samiee, Sohelila et al. (2019) Phase-amplitude coupling.
Nov. https://neuroimage.usc.edu/brainstorm/Tutorials/TutPac
Vaz, Alex P. et al. (2020). Replay of cortical spiking
sequences during human memory retrieval. Science. 367,1131-1134.
