Добавил:
Sekretar
kiopkiopkiop18@yandex.ru
t.me/Prokururor I Вовсе не секретарь, но почту проверяю
Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз:
Предмет:
Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_24_библиотеки_им_акад_М_И_Перельмана
.pdf
510
https://t.me/medicina_free
P. Cabaraux and M. Manto
Mathie MJ, Coster AC, Lovell NH, Celler BG (2004) Accelerometry:
providing an integrated, practical method for long-term, ambulatory monitoring of human movement. Physiol Meas 25(2):R1–R20.
https://doi.org/10.1088/0967- 3334/25/2/r01
Mitoma H, Hayashi R, Yanagisawa N, Tsukagoshi H (2000)
Characteristics of parkinsonian and ataxic gaits: a study using
surface electromyograms, angular displacements and oor reaction forces. J Neurol Sci 174(1):22–39. https://doi.org/10.1016/
s0022- 510x(99)00329- 9
Möhwald K, Wuehr M, Schenkel F, Feil K, Strupp M, Schniepp R
(2020) The gait disorder in primary orthostatic tremor. J Neurol
267(S1):285–291. https://doi.org/10.1007/s00415- 020- 10177- y
Molinari M (2016) Sequencing. In: Gruol D, Koibuchi N, Manto
M, Molinari M, Schmahmann J, Shen Y (eds) Essentials of cerebellum and cerebellar disorders. Springer, Cham. https://doi.
org/10.1007/978- 3- 319- 24551- 5_54
Portaro S, Russo M, Bramanti A, Leo A, Billeri L, Manuli A, La Rosa
G, Naro A, Calabrò RS (2019) The role of robotic gait training and
tDCS in Friedrich ataxia rehabilitation. Medicine 98(8):e14447.
https://doi.org/10.1097/md.0000000000014447
Rao AK, Louis ED (2019) Ataxic gait in essential tremor: a disease-
associated feature? Tremor Other Hyperkinet Mov 9. https://doi.
org/10.5334/tohm.507
Rennie DJ, Atteld SF, Morton RE, Polak FJ, Nicholson J (2000)
An evaluation of lycra garments in the lower limb using 3-D gait
analysis and functional assessment (PEDI). Gait Posture 12(1):1–6.
https://doi.org/10.1016/s0966- 6362(00)00066- 7
Renneboog B, Musch W, Vandemergel X, Manto MU, Decaux G (2006)
Mild chronic hyponatremia is associated with falls, unsteadiness,
and attention decits. Am J Med 119(1):71.e1–71.e8. https://doi.
org/10.1016/j.amjmed.2005.09.026
Schmahmann JD, Gardner R, MacMore J, Vangel MG (2009)
Development of a brief ataxia rating scale (BARS) based on a modied form of the ICARS.Mov Disord 24(12):1820–1828. https://doi.
org/10.1002/mds.22681
Schniepp R, Wuehr M, Schlick C, Huth S, Pradhan C, Dieterich M,
Brandt T, Jahn K (2014) Increased gait variability is associated
with the history of falls in patients with cerebellar ataxia. J Neurol
261(1):213–223. https://doi.org/10.1007/s00415-013-7189-3
Setta F, Jacquy J, Hildebrand J, Manto M.-U (1998) Orthostatic tremor
associated with cerebellar ataxia. J Neurol 245(5):299–302. https://
doi.org/10.1007/s004150050222
Shirai S, Yabe I, Takahashi-Iwata I, Matsushima M, Ito YM, Takakusaki
K, Sasaki H (2019) The responsiveness of triaxial accelerometer
measurement of gait ataxia is higher than that of the scale for the
assessment and rating of ataxia in the early stages of spinocerebellar degeneration. Cerebellum (London, England) 18(4):721–730.
https://doi.org/10.1007/s12311- 019- 01025- 5
Summa S, Schirinzi T, Bernava GM, Romano A, Favetta M, Valente
EM, Bertini E, Castelli E, Petrarca M, Pioggia G, Vasco G
(2020) Development of SaraHome: a novel, well-accepted, technology-based assessment tool for patients with ataxia. Comput
Methods Programs Biomed 188:105257. https://doi.org/10.1016/j.
cmpb.2019.105257
Surgent OJ, Dadalko OI, Pickett KA, Travers BG (2019) Balance and
the brain: a review of structural brain correlates of postural balance
and balance training in humans. Gait Posture 71:245–252. https://
doi.org/10.1016/j.gaitpost.2019.05.011
Suzuki M, Yogo M, Morita M, Terashi H, Iijima M, Yoneyama M,
Takada M, Utsumi H, Okuma Y, Hayashi A, Orimo S, Mitoma H
(2018) A proposal for new algorithm that denes gait-induced acceleration and gait cycle in daily parkinsonian gait disorders. In: Ortiz
JH (ed) Wearable technologies. InTech. https://doi.org/10.5772/
intechopen.75483
Synofzik M, Ilg W (2014) Motor training in degenerative spinocer-
ebellar disease: ataxia-specic improvements by intensive physiotherapy and exergames. BioMed Res Int 583507. https://doi.
org/10.1155/2014/583507
Takakusaki K (2013) Neurophysiology of gait: from the spinal cord
to the frontal lobe. Mov Disord 28(11):1483–1491. https://doi.
org/10.1002/mds.25669
Thompson R, Bhatti DE, Hellman A, Doss SJ, Malgireddy K, Shou J,
Srikanth-Mysore C, Bendi S, Bertoni JM, Torres-Russotto D (2020)
Ataxia prevalence in primary orthostatic tremor. Tremor Other
Hyperkinet Mov 10(1). https://doi.org/10.5334/tohm.570
Trouillas P, Takayanagi T, Hallett M, Currier RD, Subramony SH,
Wessel K, Bryer A, Diener HC, Massaquoi S, Gomez CM,
Coutinho P, Hamida MB, Campanella G, Filla A, Schut L, Timann
D, Honnorat J, Nighoghossian N, Manyam B (1997) International
cooperative ataxia rating scale for pharmacological assessment of
the cerebellar syndrome. J Neurol Sci 145(2):205–211. https://doi.
org/10.1016/s0022- 510x(96)00231- 6
Velázquez-Pérez L, Rodriguez-Labrada R, González-Garcés Y, Arrufat-
Pie E, Torres-Vega R, Medrano-Montero J, Ramirez-Bautista B,
Vazquez-Mojena Y, Auburger G, Horak F, Ziemann U, Gomez CM
(2021) Prodromal spinocerebellar ataxia type 2 subjects have quantiable gait and postural sway decits. Mov Disord 36(2):471–480.
https://doi.org/10.1002/mds.28343
Vijiaratnam N, Sirisena D, Paul E, Bertram KL, Williams DR (2018)
Measuring disease progression and disability in orthostatic tremor.
Parkinsonism Relat Disord 55:138–140. https://doi.org/10.1016/j.
parkreldis.2018.06.014
Wagner J, Stephan T, Kalla R, Brückmann H, Strupp M, Brandt T,
Jahn K (2008) Mind the bend: cerebral activations associated with
mental imagery of walking along a curved path. Exp Brain Res
191(2):247–255. https://doi.org/10.1007/s00221-008-1520-8
Wells H, Marquez J, Wakely L (2018) Garment therapy does not
improve function in children with cerebral palsy: a systematic
review. Phys Occup Ther Pediatr 38(4):395–416. https://doi.org/10.
1080/01942638.2017.1365323
Whitney D, Bhatti D, Torres-Russotto D (2018) Orthostatic tremor:
pathophysiology guiding treatment. Curr Treat Options Neurol
20(9). https://doi.org/10.1007/s11940- 018- 0524- 3
Zubair A, Cersonsky T, Kellner S, Huey ED, Cosentino S, Louis ED
(2018) What predicts mortality in essential tremor? A prospective, longitudinal study of elders. Front Neurol 9:1077. https://doi.
org/10.3389/fneur.2018.01077
The Social Cerebellum andHuman
https://t.me/medicina_free
Interactions
ElienHeleven andFrankVanOverwalle
78
Abstract
Research in the past 5years has provided growing evidence supporting the view that the posterior cerebellum is
involved in social mentalizing (i.e., theory of mind). We
investigated the hypothesis that the posterior cerebellum
builds internal action models of our social interactions to
predict how other people’s actions will be executed, and
what our most likely responses to these actions will be.
We developed novel social sequencing tasks that involved
a combination of (a) learning or generating chronological
sequences of social actions either in an explicit or implicit
manner, which (b) require social mentalizing on another
person’s mental state such as goals, beliefs, and implied
traits. Together, the fMRI results unequivocally conrm
the central role of the posterior cerebellar Crus 2 in identifying and automatizing action sequencing during social
mentalizing, and in predicting future action sequences
based on social mentalizing inferences about others.
These ndings provided the incentive to investigate noninvasive neurostimulation with healthy participants targeting the posterior cerebellum. Both transcranial
magnetic stimulation (TMS) as well as transcranial direct
current stimulation (tDCS) showed benecial effects on
social sequencing tasks, as participants generated correct
social action sequences quicker. These stimulation techniques guided by novel cerebellar social sequencing
insights might have the potential to increase posterior cerebellar plasticity and alleviate social impairments in mental disorders.
Keywords
Posterior cerebellum · Action sequencing · Social mentalizing · False beliefs · Trait inferences · Implicit learning ·
E. Heleven · F. Van Overwalle (*)
Department of Psychology and Center for Neuroscience, Vrije
Universiteit Brussel, Brussels, Belgium
e-mail: Elien.Heleven@vub.be; Frank.VanOverwalle@vub.ac.be
Action prediction · Non-invasive neurostimulation
Transcranial magnetic stimulation (TMS) · Transcranial
direct current stimulation (tDCS)
Human interaction is highly dependent on the ability to cor-
rectly process, interpret, and react to other persons’ behav-
iors in social situations. A key ability in interpreting social
interactions is understanding the mental state of other per-
sons, such as their intentions, beliefs, preferences, and per-
sonality traits. This is called mentalizing or theory of mind
(for meta-analyses, see Schurz etal. 2014; Van Overwalle
2009). Engaging in successful social encounters relies on
learning from our past experiences, which prepares us to
anticipate similar social interactions in the future. Social
learning is in many respects similar to other types of learning
such as the coordination of movements or cognitive proce-
dures (Brown and Brüne 2012; Rushworth etal. 2009). It is
an ongoing process that creates and strengthens internal neu-
ral representations of frequently processed sequences of
observations, movements, or actions. The cerebellum is a
key region in implicitly (i.e., with little awareness) automa-
tizing and ne-tuning of such internal representations of
recurring event sequences in time and space (Leggio and
Molinari 2015). These representations allow us to recognize
familiar events sequences so that we immediately know how
to move and act appropriately. Importantly, it also allows to
identify discrepant event sequences which are atypical or
new (Stoodley and Tsai 2021). When such unanticipated
event sequences occur, the cerebellum issues error signals
that motivate the rapid adjustment of ongoing behavior. If
these discrepant events recur, this leads to the creation of
novel or adjusted cerebellar internal representations (Heleven
etal. 2019; Ferrari etal. 2018; Pu etal. 2020). In a social
context, for example, the observation of unfriendly behavior
performed by a person to whom we thought was ‘friendly,’
can lead to the adjustment of our trait representation of this
person, and the anticipation of more unfriendly behaviors by
this person in the future. Or, if we realize that this person’s
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
D. L. Gruol et al. (eds.), Essentials of Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-031-15070-8_78
511
512
https://t.me/medicina_free
E. Heleven and F. Van Overwalle
reaction was triggered by a remark, we might add to our representation that the person is also ‘touchy,’ and adjust our
social interaction sequences with this person by adding
soothing behaviors, which leads to more desirable social
outcomes.
The cerebellum is highly connected to the cerebral cortex
(Buckner etal. 2011). The relatively uniform anatomy and
physiology of the cerebellum has given rise to the idea that
this structure performs the same computational function
across diverse domains (Diedrichsen etal. 2019). While the
cortical brain areas are considered to be involved in the initial processing of information along seven major domains or
networks (Yeo etal. 2011), the cerebellar areas connected to
them are considered to be involved in the sequential processing and coordination of this domain-specic information,
leading to automatization in time and space. This cerebellocortical connectivity is accomplished via closed-loop links,
starting from a specic location in the cerebral cortex to a
specic area in the cerebellum, and back to the same cortical
location. The cerebellum thus borrows its functional specialization from its specic connectivity with the cerebral cortex
(Buckner etal. 2011).
In this chapter, we focus on the cerebellar network
involved in social mentalizing. Researchers demonstrated
that the posterior cerebellum is mainly involved in processing social information (meta-analyses by Van Overwalle
etal. 2014, 2015a). In particular, the posterior part of the
cerebellum known as Crus 2 is preferentially engaged during
social mentalizing (meta-analysis by Van Overwalle et al.
2020; see Fig. 78.1). Neuroscientists have convincingly
shown that there are functional connections between Crus 2
and the mentalizing network in the cortex. Specically,
social mentalizing recruits a circuitry of closed-loops
Fig. 78.1 Top (transversal) view of the cerebellum with the mentalizing network marked in white. The centers of the areas in the bilateral
Crus 2, which are preferentially engaged during social sequencing
tasks, are marked in blue as 1 and 2 with MNI coordinates ±25−75−40.
Adapted from Van Overwalle etal. (2020)
between the posterior cerebellar Crus 2 and the temporo-
parietal junction, and via the latter to the medial prefrontal
cortex, two key areas in the cortical mentalizing network
(Van Overwalle etal. 2015b).
78.1 The Social Sequencing Function
ofthePosterior Cerebellar Crus 2
But what is the specic function of posterior cerebellar Crus
2? One major hypothesis is that, in line with the uniform
function of the cerebellum in (implicit) learning and automatizing of event sequences, Crus 2 is involved in identifying
sequences of social events that require mentalizing about
other persons. In order to demonstrate this domain-specic
mentalizing functionality, new mentalizing tasks have been
developed that allowed us to directly investigate social
sequencing for different aspects of mentalizing.
The rst tasks that were developed for this purpose were
the Picture and Verbal Sequencing tasks, based on earlier
work (Langdon and Coltheart 1999; Baron-Cohen et al.
1986, 1999). In both tasks, participants view four events of a
story (presented as cartoon-like pictures, see Fig.78.2; or
sentences) in a random order and are instructed to put them
in their correct chronological order. A particular aspect of
these stories is that they involve others’ false beliefs, this is,
when an agent has a different interpretation and representation of reality because this reality changed unbeknownst to
them (for an example, see Fig. 78.2). In contrast, in true
belief stories an agent is aware of this changed reality.
Understanding false beliefs requires distinguishing others’
beliefs from one’s own (Kampis etal. 2017; Wimmer and
Perner 1983).
An fMRI study by Heleven etal. (2019) demonstrated
that healthy participants show more posterior cerebellar activation when putting false or true belief stories in their correct
order as compared to social scripts or mechanical stories,
suggesting that processing of non-routine social belief
sequences recruits more cerebellar activation as compared to
routine (social or non-social) sequences. Moreover, story
sequencing resulted in more cerebellar activation than a nonsequencing control task in which the story events were presented in the correct chronological order. This is in line with
a previous study by Van Overwalle etal. (2019) which demonstrated that cerebellar patients perform less accurately
than healthy control participants on the Picture Sequencing
task when putting false belief event sequences in their correct order as compared to social scripts or mechanical stories. Both studies highlight the involvement of the cerebellum
in mentalizing-related sequence processing regarding other
persons’ beliefs.
In order to further investigate the social sequential functionality of the posterior cerebellum, a series of novel
78 The Social Cerebellum andHuman Interactions
https://t.me/medicina_free
513
Fig. 78.2 Picture sequencing task. An example of a false-belief
sequence. (The correct order is 2—1—4—3: a boy checks the last chocolate in a box—goes playing and leaves the box unattended—mean-
sequencing tasks were developed. In these tasks social
sequencing was compared against two control conditions
involving either (1) social non-sequencing and (2) non-
social sequencing. Thus, eshing out both the sequencing
and social functionality of the posterior cerebellum.
Figure78.3 depicts a number of these novel tasks involving
the combination of sequencing and a variety of mentalizing
aspects such as others’ goal-directed intentions (Li et al.
2021), traits of others (Pu etal. 2020), and trait-related pre-
dictions (Haihambo etal. 2021; not shown), not only at an
explicit level, but also at an implicit level (Ma etal. 2021a).
These tasks were explored in a series of neuroimaging studies on healthy participants, using fMRI.
• A rst aspect of social mentalizing that was investigated
is goal-directed navigation (Li etal. 2021; Fig.78.3a). In
this task, participants observed a human-like agent (i.e.,
smurf) navigating through a grid towards a desired goal.
They were instructed to memorize and subsequently replicate the trajectory of the agent. In the control conditions,
they merely observed this without memorizing the trajectory (non-sequencing control) or they observed a ball rolling down and randomly following the same trajectory due
to the uneven terrain (non-social control).
• Trait-implying action processing is a second aspect of
social mentalizing that was investigated (Pu etal. 2020;
Fig.78.3b). In this task, participants viewed a series of
behavioral descriptions that implied a personality trait
about a person, and were instructed to memorize and
recall the temporal order of these behaviors, and to infer
the implied trait. For instance, giving rst a compliment,
then buying a present, and next picking up a book for
someone; these distinct actions all imply kindness as a
trait. In control conditions, the order of behaviors had not
to be memorized (non-sequential control), or objects were
described that implied the same characteristic (non-social
control).
• A third aspect investigated was trait-related prediction.
Haihambo etal. (2021) explored this question by reversing the task logic of the trait study by Pu etal. (2020)
described above. Participants were rst given the trait of a
protagonist (e.g., Fumak is dishonest), and then they had
while a girl discovers the last chocolate and eats it—on his return, the
boy is surprised to nd the box empty; from Langdon and Coltheart
1999; see also Baron-Cohen etal. 1986; Heleven etal. 2019)
a
b
c
Fig. 78.3 (a) Goal-directed trajectories: An example of a trial depict-
ing a smurf moving along a trajectory from start (denoted by “S”) to end
(“E”) shown in gray (characters and gray not shown to the participants; Li
etal. 2021). (b) Trait-implying Action Sequences: An example of a trial
with six sentences implying a trait of which the order had to be memorized (Pu et al. 2020). (c) Implicit Belief Serial Response Time:
Participants had to answer as fast as possible how many owers the smurf
could see when oriented to the owers; and when not, how many owers
he or she had seen previously. Unbeknownst to them, there was a xed
order of true and false beliefs held by the smurfs (Ma etal. 2021b)
514
cd
https://t.me/medicina_free
ab
E. Heleven and F. Van Overwalle
Fig. 78.4 fMRI contrasts for various mentalizing sequencing tasks
revealing activation in the posterior cerebellum. (a) Goal-directed
Trajectories (Li etal. 2021). (b) Trait-implying Action Sequences (Pu
to select four out of six possible actions that were consistent with the trait information and put them in the correct
chronological order.
• A fourth investigated aspect is implicit sequence processing (Ma etal. 2021a). Testing implicit social learning is
important, because as we stated in our introduction, the
cerebellum is necessary for implicit learning and automatization. In the novel Belief Serial Response Time (SRT)
task developed by Ma etal. (2021a), participants were
requested to identify true and false beliefs of two humanlike agents. Participants saw one of two smurfs, receiving
owers at four xed locations on top of the screen
(Fig.78.3c), and were requested to report how many owers the smurf thought to have received. The smurf held a
true belief when he or she was oriented toward the owers
and a potential false belief when oriented away from the
owers. In the latter case, the correct answer was the
number of owers the smurf thought to have received the
last time he or she held a true belief. Unbeknownst to the
participants, there was a standard sequence of these true–
false beliefs which was repeated over the course of the
experiment. This is a crucial aspect of an SRT task (Nissen
and Bullemer 1987), because repeating the same sequence
of stimuli over time typically shows faster responding
over time, demonstrating implicit learning. Moreover,
when the standard sequence is interrupted by random
orders, the response time goes up again.
Figure 78.4 depicts the main neuroimaging results of
these novel tasks. As can be seen, the critical social sequencing condition showed stronger recruitment in the posterior
cerebellar Crus for goal-directed intentions (Li etal. 2021;
Fig.78.4a), trait-implying actions of others (Pu etal. 2020;
Fig. 78.4b), and trait-based action prediction (Haihambo
etal. 2021; Fig.78.4c) in comparison with non-sequencing
control conditions where participants only observed trajectories or read trait sentences, without memorizing or generating their order. Comparisons against the non-social control
etal. 2020). (c) Trait-based Action Prediction (Haihambo etal. 2021).
(d) Implicit Belief Serial Response Time (Ma etal. 2021b)
conditions showed similar activation of the posterior cerebellar Crus. In the Belief SRT task (Ma et al. 2021b;
Fig.78.4d), a comparison of standard sequences at the later
“test” phase (with occasional interruptions by random
sequences so that the standard sequence had to be reinstated)
versus the earlier “training” phase (with only standard
sequences) showed similar recruitment of the posterior cerebellar Crus. Taken together, this series of fMRI studies conrms the posterior cerebellar involvement in different aspects
of social mentalizing-related sequence processing. These
ndings are in line with the hypothesized function of the
posterior cerebellum: learning, automatizing, and ne- tuning
of internal representations of social sequence information
that requires mentalizing.
78.2 Clinical Implications
The importance of research on social mentalizing-related
sequence processing becomes apparent when we consider
the clinical implications of these studies. It has been demonstrated that decits in the posterior cerebellum may play a
crucial role in the onset and maintenance of psychiatric disorders related to mentalizing decits, such as autism spec-
trum disorder (D’Mello et al. 2015; Olivito et al. 2018;
Velikonja et al. 2019), depression (Bora and Berk 2016;
Schutter 2016), bipolar disorder(Lupo et al. 2021), obses-
sive compulsive disorder (Jansen etal. 2020; Narayanaswamy
etal. 2016; Xu etal. 2019; Zhang et al. 2019), addiction
(Kornreich etal. 2013; Maurage etal. 2011; Miquel etal.
2016; Onuoha etal. 2016) and schizophrenia (Bernard and
Mittal 2015; Brady etal. 2020; Moberget etal. 2018, 2019;
Pinkham 2014). The results of the novel social sequencing
tasks suggest that the posterior cerebellum may potentially
play a central role in social dysfunctions observed in many
clinical pathologies, due to impairment in social sequencing
that requires mentalizing about others (Van Overwalle et al.
2021). For each of these disorders, we can investigate which
78 The Social Cerebellum andHuman Interactions
https://t.me/medicina_free
515
aspects of social mentalizing- related sequence processing is
key. It might help clinicians to identify and understand social
problems in detail, leading to a more personal diagnoses and
treatment. The newly developed mentalizing sequencing
tasks have the potential to be helpful tools for diagnosing or
treating people with cerebellar problems in a clinical
setting.
78.3 Non-invasive Brain Stimulation
As demonstrated earlier, neuroimaging and patient studies
have consistently demonstrated that the posterior cerebellar
Crus 2 is essential in sequencing social mentalizing information, and thus suggest this cerebellar area as potential
target for treatment to improve social functioning. One
treatment directly targeting the brain is non-invasive neurostimulation such as transcranial magnetic stimulation (TMS)
and transcranial direct current stimulation (tDCS). These
techniques seem to have benecial effects on motor, cognitive, and affective problems related to the cerebellum (for a
review see Van Dun etal. 2017). In two neurostimulation
studies, the potential benets for social processing were
explored using cerebellar TMS (Heleven et al. 2021) and
cerebellar tDCS (Heleven etal. 2022). We investigated the
effects of these stimulation techniques on healthy participants’ performances on the Picture and Verbal Sequencing
tasks. The results in Fig.78.5 show that in each task, neurostimulation resulted in faster response times for putting the
events in their correct order. No such improvements were
found after sham (i.e., control) stimulation. However, these
studies did not show differential effects of cerebellar neurostimulation for different types of sequences involving
mechanical, social script, or social beliefs, except for a surprising lack of effect for false-belief sequences in the tDCS
study. A number of parameters of the studies such as the
focus of the stimulation and statistical power can explain
these non-specic or unexpected results. Follow-up research
taking into account limitations of these preliminary studies
is needed in order to obtain more convincing results.
Moreover, we would expect differential neurostimulation
effects for different types of sequences (i.e., mechanical,
social script, or social beliefs) when investigating different
psychiatric populations with distinct cerebellar problems
related to social mentalizing. These groups should therefore
be included in future studies.
Taken together, neuroscientic research has convincingly
shown a role for the cerebellum in social mentalizing
sequencing. Newly developed tasks allow us to investigate
different aspects of mentalizing-related sequences such as
goal-directed navigation, trait processing, trait-based prediction, and implicit automatization of belief processing.
Research on this topic is ongoing and promising, and will
continue to contribute to our understanding and treatment of
human interaction related to the social cerebellum. As
always, future investigation is needed to increase our insight
in the underlying cerebellar mechanisms and potential applications for improving successful social interaction.
10.0
9.8
9.6
9.6
9.2
9.0
8.8
Fig. 78.5 (Left) Logged response times pre (blue) and post (orange)
TMS per story type for the Picture Sequencing task (Heleven etal.
2021). (Right) Response times pre (blue) and post (orange) anodal
tDCS for Picture Sequencing (preliminary data). Asterisks indicate sig-
***
***
***
False Belief Tr ue Belief Social Scriot
Pre TMS Pre tDCSPost TM ost tDCS
***
Mechanical
SP
15 sec
*
*
10 sec
5 sec
False Belief Tr ue Belief Social Script Mechanical
nicant differences from pre to post stimulation using a two-sided t-test
with ∗ p<0.05, ∗∗∗ p<0.001. In both sham conditions, pre to post
differences were almost all non-signicant
*
516
https://t.me/medicina_free
E. Heleven and F. Van Overwalle
References
Baron-Cohen S, Leslie AM, Frith U (1986) Mechanical, behavioural
and Intentional understanding of picture stories in autistic children.
Br J Dev Psychol 4(2):113–125. https://doi.org/10.1111/j.2044-
835x.1986.tb01003.x
Baron-Cohen S, O’Riordan M, Stone V, Jones R, Plaisted K (1999)
Recognition of faux pas by normally developing children and children with asperger syndrome or high-functioning autism. J Autism
Dev Disord 29(5):407–418
Bernard JA, Mittal VA (2015) Dysfunctional activation of the cerebel-
lum in schizophrenia. Clin Psychol Sci 3(4):545–566. https://doi.
org/10.1177/2167702614542463
Bora E, Berk M (2016) Theory of mind in major depressive disorder: a
meta-analysis. J Affect Disord 191:49–55. https://doi.org/10.1016/j.
jad.2015.11.023
Brady RO, Beermann A, Nye M, Eack SM, Mesholam-Gately R,
Keshavan MS, Lewandowski KE (2020) Cerebellar-cortical connectivity is linked to social cognition trans-diagnostically. Front
Psych 11:573002. https://doi.org/10.3389/fpsyt.2020.573002
Brown EC, Brüne M (2012) The role of prediction in social neu-
roscience. Front Hum Neurosci 6:147. https://doi.org/10.3389/
fnhum.2012.00147
Buckner RL, Krienen FM, Castellanos A, Diaz JC, Thomas Yeo BT
(2011) The organization of the human cerebellum estimated by
intrinsic functional connectivity. J Neurophysiol 106(5):2322–2345.
https://doi.org/10.1152/jn.00339.2011
D’Mello AM, Crocetti D, Mostofsky SH, Stoodley CJ (2015) Cerebellar
gray matter and lobular volumes correlate with core autism
symptoms. NeuroImage 7:631–639. https://doi.org/10.1016/j.
nicl.2015.02.007
Diedrichsen J, King M, Hernandez-Castillo C, Sereno M, Ivry RB (2019)
Universal transform or multiple functionality? Understanding the
contribution of the human cerebellum across task domains. Neuron
102(5):918–928. https://doi.org/10.1016/j.neuron.2019.04.021
Ferrari C, Oldrati V, Gallucci M, Vecchi T, Cattaneo Z (2018) The
role of the cerebellum in explicit and incidental processing of
facial emotional expressions: a study with transcranial magnetic
stimulation. NeuroImage 169:256–264. https://doi.org/10.1016/j.
neuroimage.2017.12.026
Haihambo N, Ma Q, Baeken C, Deroost N, Baetens K, Heleven E,
Van Overwalle F (2021) Social thinking is for doing: the posterior
cerebellum supports prediction of social actions based on personality traits. Soc Cogn Affect Neurosci 17(2):241–251. https://doi.
org/10.1093/scan/nsab087
Heleven E, van Dun K, Van Overwalle F (2019) The posterior cer-
ebellum is involved in constructing social action sequences:
an fMRI study. Sci Rep 9(1):11110. https://doi.org/10.1038/
s41598- 019- 46962- 7
Heleven E, van Dun K, De Witte S, Baeken C, Van Overwalle F (2021)
The role of the cerebellum in social and non-social action sequences:
a preliminary LF-rTMS study. Front Hum Neurosci 15:593821
Heleven E, Ma Q, Daineffe LB, Vazquez MG, Deroost N, Baetens K,
Baeken C (2022) The effect of Cerebellar tDCS on Picture and
Verbal Action Sequencing. Unpublished data
Jansen M, Overgaauw S, De Bruijn ERA (2020) Social cognition
and obsessive-compulsive disorder: a review of subdomains of
social functioning. Front Psych 11:118. https://doi.org/10.3389/
fpsyt.2020.00118
Kampis D, Fogd D, Kovács ÁM (2017) Nonverbal components of
Theory of Mind in typical and atypical development. Infant Behav
Dev 48:54–62. https://doi.org/10.1016/j.infbeh.2016.11.001
Kornreich C, Brevers D, Canivet D, Ermer E, Naranjo C, Constant
E et al (2013) Impaired processing of emotion in music,
faces and voices supports a generalized emotional decod-
ing decit in alcoholism. Addiction 108(1):80–88. https://doi.
org/10.1111/j.1360- 0443.2012.03995.x
Langdon R, Coltheart M (1999) Mentalising, schizotypy, and schizo-
phrenia. Cognition 71:43–71
Leggio M, Molinari M (2015) Cerebellar sequencing: a trick for pre-
dicting the future. Cerebellum 14(1):35–38. https://doi.org/10.1007/
s12311- 014- 0616- x
Li M, Ma Q, Baetens K, Pu M, Deroost N, Baeken C etal (2021) Social
cerebellum in goal-directed navigation. Soc Neurosci 16(5):467–
485. https://doi.org/10.1080/17470919.2021.1970017
Lupo M, Olivito G, Gragnani A, Saettoni M, Siciliano L, Pancheri
C et al (2021) Comparison of cerebellar grey matter altera-
tions in bipolar and cerebellar patients: evidence from voxel-
based analysis. Int J Mol Sci 22(7):3–7. https://doi.org/10.3390/
ijms22073511
Ma Q, Heleven E, Funghi G, Pu M, Baetens K, Deroost N, Van Overwalle
F (2021a) Implicit learning of true and false belief sequences. Front
Psychol 12:643594. https://doi.org/10.3389/fpsyg.2021.643594
Ma Q, Pu M, Heleven E, Haihambo NP, Baetens K, Baeken C etal
(2021b) The posterior cerebellum supports implicit learning of
social belief sequences. Cogn Affect Behav Neurosci 21(5):970–
992. https://doi.org/10.3758/s13415- 021- 00910- z
Maurage P, Grynberg D, Noël X, Joassin F, Philippot P, Hanak C
et al (2011) Dissociation between affective and cognitive empa-
thy in alcoholism: a specic decit for the emotional dimen-
sion. Alcohol Clin Exp Res 35(9):1662–1668. https://doi.
org/10.1111/j.1530- 0277.2011.01512.x
Miquel M, Vazquez-Sanroman D, Carbo-Gas M, Gil-Miravet I,
Sanchis-Segura C, Carulli D etal (2016) Have we been ignoring the
elephant in the room? Seven arguments for considering the cerebel-
lum as part of addiction circuitry. Neurosci Biobehav Rev 60:1–11.
https://doi.org/10.1016/j.neubiorev.2015.11.005
Moberget T, Doan NT, Alnæs D, Kaufmann T, Córdova-Palomera A,
Lagerberg TV etal (2018) Cerebellar volume and cerebellocerebral
structural covariance in schizophrenia: a multisite mega-analysis of
983 patients and 1349 healthy controls. Mol Psychiatry 23(6):1512–
1520. https://doi.org/10.1038/mp.2017.106
Moberget T, Alnæs D, Kaufmann T, Doan NT, Córdova-Palomera A,
Norbom LB et al (2019) Cerebellar gray matter volume is asso-
ciated with cognitive function and psychopathology in adoles-
cence. Biol Psychiatry 86(1):65–75. https://doi.org/10.1016/j.
biopsych.2019.01.019
Narayanaswamy JC, Jose D, Kalmady SV, Agarwal SM,
Venkatasubramanian G, Janardhan Reddy YC (2016) Cerebellar
volume decits in medication-naïve obsessive compulsive dis-
order. Psychiatry Res Neuroimaging 254:164–168. https://doi.
org/10.1016/j.pscychresns.2016.07.005
Nissen MJ, Bullemer P (1987) Attentional requirements of learning:
evidence from performance measures. Cogn Psychol 32(1):1–32.
https://doi.org/10.1016/0010- 0285(87)90002- 8
Olivito G, Lupo M, Laghi F, Clausi S, Baiocco R, Cercignani M etal
(2018) Lobular patterns of cerebellar resting-state connectivity in
adults with Autism Spectrum Disorder. Eur J Neurosci 47(6):729–
735. https://doi.org/10.1111/ejn.13752
Onuoha RC, Quintana DS, Lyvers M, Guastella AJ (2016) A meta-
analysis of theory of mind in alcohol use disorders. Alcohol Alcohol
51(4):410–415. https://doi.org/10.1093/alcalc/agv137
Pinkham AE (2014) Social cognition in schizophrenia. J Clin Psychiatry
75(SUPPL. 2):14–19. https://doi.org/10.4088/JCP.13065su1.04
Pu M, Heleven E, Delplanque J, Gibert N, Ma Q, Funghi G, Van
Overwalle F (2020) The posterior cerebellum supports the explicit
sequence learning linked to trait attribution. Cogn Affect Behav
Neurosci 20(4):798–815
Rushworth MF, Mars RB, Summereld C (2009) General mechanisms
for making decisions? Curr Opin Neurobiol 19(1):75–83. https://
doi.org/10.1016/j.conb.2009.02.005
78 The Social Cerebellum andHuman Interactions
https://t.me/medicina_free
517
Schurz M, Radua J, Aichhorn M, Richlan F, Perner J (2014)
Fractionating theory of mind: a meta-analysis of functional brain
imaging studies. Neurosci Biobehav Rev 42:9–34. https://doi.
org/10.1016/j.neubiorev.2014.01.009
Schutter DJLG (2016) A cerebellar framework for predictive coding
and homeostatic regulation in depressive disorder. Cerebellum
15(1):30–33. https://doi.org/10.1007/s12311- 015- 0708- 2
Stoodley CJ, Tsai PT (2021) Adaptive prediction for social contexts:
the cerebellar contribution to typical and atypical social behaviors. Annu Rev Neurosci 44:475–493. https://doi.org/10.1146/
annurev- neuro- 100120- 092143
Van Dun K, Bodranghien F, Manto M, Mariën P (2017)
Targeting the cerebellum by noninvasive neurostimulation: a
Review. Cerebellum 16(3):695–741. https://doi.org/10.1007/
s12311-016-0840-7
Van Overwalle F (2009) Social cognition and the brain: a meta-
analysis. Hum Brain Mapp 30(3):829–858. https://doi.org/10.1002/
hbm.20547
Van Overwalle F, Baetens K, Mariën P, Vandekerckhove M (2014)
Social cognition and the cerebellum: a meta-analysis of over 350
fMRI studies. NeuroImage 86:554–572. https://doi.org/10.1016/j.
neuroimage.2013.09.033
Van Overwalle F, Baetens K, Mariën P, Vandekerckhove M (2015a)
Cerebellar areas dedicated to social cognition? A comparison of
meta-analytic and connectivity results. Soc Neurosci 10(4):337–
344. https://doi.org/10.1080/17470919.2015.1005666
Van Overwalle F, D’aes T, Mariën P (2015b) Social cognition and
the cerebellum: a meta-analytic connectivity analysis. Hum Brain
Mapp 36(12):5137–5154. https://doi.org/10.1002/hbm.23002
Van Overwalle F, De Coninck S, Heleven E, Perrotta G, Taib NOB,
Manto M, Mariën P (2019) The role of the cerebellum in recon-
structing social action sequences: a pilot study. Soc Cogn Affect
Neurosci 14(5):549–558. https://doi.org/10.1093/scan/nsz032
Van Overwalle F, Ma Q, Heleven E (2020) The posterior crus II
cerebellum is specialized for social mentalizing and emotional
self- experiences: a meta-analysis. Soc Cogn Affect Neurosci
15(9):905–928. https://doi.org/10.1093/scan/nsaa124
Van Overwalle F, Baeken C, Campanella S, Crunelle CL, Heleven E,
Kornreich C, Baetens K (2021) The role of the posterior cerebel-
lum in dysfunctional social sequencing. Cerebellum (0123456789).
https://doi.org/10.1007/s12311-021-01330-y
Velikonja T, Fett AK, Velthorst E (2019) Patterns of nonso-
cial and social cognitive functioning in adults with autism
spectrum disorder: a systematic review and meta-analysis.
JAMA Psychiat 76(2):135–151. https://doi.org/10.1001/
jamapsychiatry.2018.3645
Wimmer H, Perner J (1983) Beliefs about beliefs: representation and
constraining function of wrong beliefs in young children’s under-
standing of deception. Cognition 13:103–128
Xu T, Zhao Q, Wang P, Fan Q, Chen J, Zhang H etal (2019) Altered rest-
ing-state cerebellar-cerebral functional connectivity in obsessive-
compulsive disorder. Psychol Med 49(07):1156–1165. https://doi.
org/10.1017/S0033291718001915
Yeo BTT, Krienen FM, Sepulcre J, Sabuncu MR, Lashkari D,
Hollinshead M etal (2011) The organization of the human cerebral
cortex estimated by intrinsic functional connectivity. J Neurophysiol
106(3):1125–1165. https://doi.org/10.1152/jn.00338.2011
Zhang H, Wang B, Li K, Wang X, Li X, Zhu J etal (2019) Altered func-
tional connectivity between the cerebellum and the cortico- striato-
thalamo-cortical circuit in obsessive-compulsive disorder. Front
Psych 10:1–8. https://doi.org/10.3389/fpsyt.2019.00522
Part X
https://t.me/medicina_free
Human Cerebellar Disorders: From Prenatal
Period to Elderly
Genetics andDifferential Diagnosis
https://t.me/medicina_free
ofCerebellar Ataxias
FrancescPalau andJavierArpa
79
Abstract
Ataxias are a complex and heterogeneous group of disorders characterized by the absence of order and coordination of voluntary movements and loss of equilibrium.
The major clinical criteria for diagnosis include disease
extension (focal vs non-focal), etiology (hereditary vs
symptomatic or idiopathic), progression rate, age at
onset, and neurological cognitive and psychiatric disorders, dysmorphic elements and systemic symptoms
which can guide the molecular diagnosis of specic disorders. Age at onset is a very important clinical tool that
along with inheritance and genetic testing is useful to
address the proper differential diagnosis. In this way,
four major categories of cerebellar ataxias may be recognized: (1) congenital ataxias, (2) early onset in infancy
(<2 years), (3) onset in childhood, adolescence, and
young adulthood (<25years), and (4) late-onset cerebellar ataxias. Genetics and genomics have become important tools for diagnosis and genetic counseling, and to
dene molecular pathways and targets for the development of new therapies.
F. Palau (*)
Department of Genetic & Molecular Medicine and Pediatric
Institute of Rare Diseases (IPER), Sant Joan de Déu Children’s
Hospital and Research Institute, Barcelona, Spain
CIBER on Rare Diseases (CIBERER), Instituto de Salud Carlos
III, Barcelona, Spain
Division of Pediatrics, University of Barcelona School of Medicine
and Health Sciences, Barcelona, Spain
e-mail: francesc.palau@sjd.es
J. Arpa
Department of Anatomy, Histology and Neurosciences,
Autonomous University of Madrid School of Medicine,
Madrid, Spain
Instituto de Investigación Sanitaria del Hospital Universitario La
Paz (IDIPAZ), Madrid, Spain
Keywords
Cerebellar ataxias · Inheritance · Genetics · Differential
diagnosis · Congenital ataxias · Cerebellar ataxias in
infancy · Cerebellar ataxias in childhood · Cerebellar
ataxias in adolescence · Cerebellar ataxias in young
adulthood · Late-onset cerebellar ataxias
79.1 Introduction
Cerebellar ataxias represent a wide group of disorders
involving cerebellar, olivo-ponto-cerebellar, or spinocerebellar systems. Classically recognition of these diseases and
nosological conditions has been based on the clinical features and associated pathology. In addition, the current
approach to cerebellar ataxias requires knowledge of their
genetic foundations, which is essential for a correct diagnosis, management, and counseling of patients and their families. A rational diagnostic approach to the ataxic patients
starts with proper orientation of the natural history of the
disease, clinical symptoms, and neurological and systemic
examinations. Critical aspects are (1) distinction between
focal (tumor, abscess, hemorrhage, ischemia, focal demyelination) and non-focal (degenerative, metabolic, toxic,
infectious, paraneoplastic syndrome) cerebellar disorder, (2)
progression rate (acute, chronic non-progressive, chronic
progressive, intermittent), (3) age at onset (early onset, late
onset), and (4) evidence for a characteristic neurological
phenotype and systemic involvement. Moreover, most of
chronic, either non-progressive congenital/developmental
ataxias or progressive degenerative ataxias, are caused by
gene mutations and segregate with a specic Mendelian or
mitochondrial (maternal) inheritance pattern as mentioned
above (Palau and Espinós 2021). Nevertheless, the cause of
the disease is not achieved in a number of sporadic patients
with idiopathic ataxia.
Modern diagnostic criteria and classication of hereditary
ataxias started in 1983 when Anita Harding (1983, 1993)
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
D. L. Gruol et al. (eds.), Essentials of Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-031-15070-8_79
521
Соседние файлы в папке Библиотека им академика М.И. Перельмана